Qureos Mentor

Tether Operations Limited

<div>Join Tether and Shape the Future of Digital Finance
At Tether, we&rsquo;re not just building products, we&rsquo;re pioneering a global financial revolution. Our cutting-edge solutions empower businesses&mdash;from exchanges and wallets to payment processors and ATMs&mdash;to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance: Our innovative product suite features the world&rsquo;s most trusted stablecoin, USDT, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that&rsquo;s just the beginning:
Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET, our flagship app that redefines secure and private data sharing.
Tether Education: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you&rsquo;re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We&rsquo;ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
Tether is seeking a highly skilled and versatile Internal Audit Manager to support the execution of its global internal audit program. The role involves independently assessing the effectiveness of internal controls, governance processes, and risk management practices across financial operations, business workflows, and technology systems.
Operating in a fast paced digital asset environment, the ideal candidate will have a strong background in operational and financial audits from a leading consulting or audit firm, coupled with hands-on experience in the digital asset sector.
This role will serve as a key member of the Internal Audit Team, shaping strategic decisions, delivering risk based insights to senior stakeholders, and building a resilient risk culture that supports long term growth.
Responsibilities
Audit Planning &amp; Execution<ul><li>
Plan and execute risk based audits across financial, operational, and technology areas in line with the internal audit plan.</li><li>
Develop audit scopes informed by enterprise risk assessments and emerging threats.</li><li>
Lead walkthroughs and direct fieldwork with structured testing, sampling, and evidence standards.</li><li>
Oversee audit working papers and workflow documentation to professional standards.</li></ul>
Controls &amp; Governance Assurance<ul><li>
Evaluate the effectiveness of internal controls and risk management practices across processes and systems.</li><li>
Assess governance, policy adherence, and regulatory compliance.</li><li>
Test design and operating effectiveness of key controls and identify gaps across the firm&rsquo;s lines of defense.</li></ul>
Technology &amp; Systems Assurance<ul><li>
Review critical systems and platforms for control design, security, and operational integrity.</li><li>
Assess application controls, access, change management, and data integrity.</li><li>
Provide independent assurance over new initiatives, system implementations, and emerging technology adoption.</li></ul>
Reporting, Remediation &amp; Stakeholder Engagement
<ul><li>Prepare audit reports and communicate findings to senior leadership and the Audit Committee.</li><li>
Provide practical, risk based recommendations and own remediation tracking through to closure.</li><li>
Collaborate with Finance, Technology, Risk, and Compliance to validate observations and escalate significant exposures.</li></ul>
Risk Culture &amp; Continuous Improvement
<ul><li>Promote a strong risk and control culture across the organization through audit engagement and awareness.</li><li>
Stay current on industry developments, emerging risks, and regulatory frameworks.</li><li>
Apply IIA standards and contribute to the evolution of audit methodologies and quality processes.</li></ul> 
Requirements<ul><li>
5&ndash;8 years of internal audit or assurance experience spanning financial, operational, and technology risk domains.
</li><li>Big 4 or top-tier consulting background strongly preferred.
</li><li>CPA or CIA required; CISA, CISM or similar strongly advantageous.
</li><li>Strong knowledge of blockchain architecture, DeFi platforms, crypto custody models, and the related IT control landscape.
</li><li>Solid grounding in financial reporting frameworks and internal control design.
</li><li>Familiarity with global digital asset regulatory frameworks.
</li><li>Sharp critical thinking and analytical skills, with the ability to translate technical issues into actionable recommendations.
</li><li>Excellent written and verbal communication, including audit report writing for senior stakeholders.
</li><li>Proven ability to work independently and deliver in a fast paced, remote first environment</li></ul>
Important information for candidates 
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:<ul><li>
Apply only through our official channels. We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/</li><li>
Verify the recruiter&rsquo;s identity. All our recruiters have verified LinkedIn profiles. If you&rsquo;re unsure, you can confirm their identity by checking their profile or contacting us through our website.</li><li>
Be cautious of unusual communication methods. We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.</li><li>
Double-check email addresses. All communication from us will come from emails ending in @tether.to or @tether.io</li><li>
We will never request payment or financial details. If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.</li></ul>
When in doubt, feel free to reach out through our official website.</div>

Internal Audit Manager (100% remote)

<div>Join Tether and Shape the Future of Digital Finance
At Tether, we&rsquo;re not just building products, we&rsquo;re pioneering a global financial revolution. Our cutting-edge solutions empower businesses&mdash;from exchanges and wallets to payment processors and ATMs&mdash;to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance: Our innovative product suite features the world&rsquo;s most trusted stablecoin, USDT, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that&rsquo;s just the beginning:
Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET, our flagship app that redefines secure and private data sharing.
Tether Education: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you&rsquo;re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We&rsquo;ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
We are developing a highly scalable media intelligence platform that processes, analyzes, and structures large volumes of multimedia content across text, image, video, and audio. As a Senior Applied ML Engineer, you will architect and build the core backend systems that power media ingestion, processing workflows, metadata generation, AI-based analysis, semantic search, and retrieval across large media libraries.
We are looking for a Senior Applied ML Engineer who can design, implement, optimize, and evaluate a production-grade moderation pipeline using open-source models.
This role requires deep backend engineering expertise, strong system design capability, and practical experience integrating AI/ML systems into production workflows. You will work on complex media-processing pipelines, video/audio analysis, OCR, speech-to-text, embedding generation, vector search, multimodal model integrations, and high-throughput asynchronous workloads. You will collaborate closely with engineering leadership to define backend architecture, improve reliability and scalability, and guide other engineers in delivering secure, observable, and high-performance systems.
Responsibilities
Backend Architecture &amp; System Ownership<ul><li>
Architect, build, and operate scalable backend services for a media intelligence platform, with a focus on clean, maintainable, and production-ready systems.</li><li>
Own critical backend components end to end, from system design and API contracts through implementation, deployment, monitoring, and iteration.</li><li>
Drive architectural decisions across APIs, processing pipelines, distributed compute, storage, search, observability, cloud infrastructure, and model-serving workflows.</li><li>
Design data models and storage patterns for media assets, generated metadata, embeddings, processing jobs, model outputs, search indexes, and audit trails.</li><li>
Design high-throughput media ingestion and processing pipelines for large volumes of video, audio, image, and text content.</li><li>
Build distributed, event-driven workflows for media processing using queues and pub/sub systems such as SQS, Kafka, Pub/Sub, or equivalent technologies.</li><li>
Implement reliable asynchronous processing patterns, including retries, idempotency, dead-letter queues, backpressure handling, and fault-tolerant job execution.</li></ul>
AI/ML Integration &amp; Model Workflows<ul><li>
Lead the development and optimization of metadata extraction, content analysis, scene detection, transcription, embedding generation, and multimodal AI inference workflows.</li><li>
Integrate and optimize AI/ML services within backend workflows, including model APIs, embedding pipelines, OCR, speech-to-text, scene analysis, multimodal inference, batching, caching, and fallback strategies.</li><li>
Collaborate with ML engineers, data scientists, or external model providers to benchmark models, compare quality/latency trade-offs, and safely roll out model upgrades.</li></ul>
Model Serving &amp; Performance Optimization<ul><li>
Optimize AI/ML inference workflows for latency, throughput, reliability, and cost across both real-time and batch-processing paths.</li><li>
Work with model-serving systems such as vLLM, Triton, TGI, SageMaker, Vertex AI, or custom inference services to improve batching, concurrency, warmup behavior, timeout handling, autoscaling, and GPU utilization.</li><li>
Evaluate and apply practical model optimization techniques such as quantization, model distillation, batching, caching, prompt optimization, and routing to smaller or cheaper models where appropriate.</li><li>
Design and maintain vector search and indexing systems using technologies such as Pinecone, Weaviate, Qdrant, Elastic Vectors, FAISS, pgvector, or similar tools.</li><li>
Build retrieval workflows that support semantic search, similarity matching, duplicate detection, media discovery, and structured metadata search.</li><li>
Monitor model and system performance in production, including API latency, queue depth, processing time, model error rates, GPU utilization, confidence distributions, drift signals, and cost per processed item.Search, Indexing &amp; Data Retrieval</li></ul>
Infrastructure, Reliability &amp; Observability<ul><li>
Deploy and operate systems on AWS, GCP, Azure, or equivalent cloud platforms, including compute, storage, networking, queues, model-serving infrastructure, and monitoring systems.</li><li>
Ensure system reliability through logging, metrics, tracing, alerting, dashboards, operational runbooks, and incident-response best practices.</li></ul>
Collaboration &amp; Engineering Leadership<ul><li>
Collaborate with product, design, data, and ML teams to deliver media-rich, AI-powered product features.</li><li>
Mentor junior and mid-level engineers, support technical planning, review designs, and raise engineering quality across the team.</li><li>
Participate in code reviews, documentation, technical planning, and continuous improvement of engineering practices.</li><li>
Ensure code quality through testing, peer review, clear documentation, and maintainable implementation patterns.</li></ul> 
Education &amp; Experience<ul><li>
Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.</li><li>
5-7+ years of backend engineering experience, ideally building scalable distributed systems, media platforms, data pipelines, or high-throughput backend services.</li><li>
Prior experience owning major backend modules end to end, including architecture, implementation, deployment, monitoring, and production operations.</li><li>
3 + years of experience integrating AI/ML inference systems into backend workflows, including model APIs, embedding pipelines, OCR, speech-to-text, scene detection, or multimodal model outputs.</li><li>
Hands-on experience creating AI-powered processing pipelines for image, video, audio, or text analysis.</li><li>
Practical experience with production model optimization, especially for image, video, embedding, or multimodal models, including batching, caching, quantization, prompt optimization, routing strategies, latency reduction, and cost optimization.</li><li>
Prior experience with vector search, semantic search, media retrieval, or similarity-matching systems is strongly preferred.</li><li>
Experience mentoring engineers, leading technical discussions, and influencing architectural decisions across backend, infrastructure, and AI/ML workflows.</li></ul>
Technical Skills<ul><li>
Strong expertise in Python and/or Node.js with Deep understanding of building scalable RESTful APIs and backend architectures</li><li>
Experience with HuggingFace transformers ecosystem and deep learning frameworks such as PyTorch and TensorFlow.</li><li>
Strong experience with SQL/NoSQL databases, schema design, and data modeling</li><li>
Preferred Exposure to distributed systems, microservices, asynchronous processing, and event-driven patterns with SQS, Pub/Sub, Kafka, or other queueing/pub-sub systems</li><li>
Experience deploying production systems on AWS, GCP, or similar cloud platforms</li><li>
Knowledge of infrastructure patterns (compute, storage, networking, observability)</li></ul>
AI/ML Integration<ul><li>
Experience orchestrating embedding generation, scene detection, OCR, speech-to-text, image classification, video analysis, and multimodal model integrations.</li><li>
Experience optimizing inference workflows for latency, throughput, reliability, and cost.</li><li>
Experience working with scalable and optimized inference settings, including tuning sampling parameters, managing output‑length formats, and configuring reasoning‑related behaviors.</li><li>
Familiarity with practical model optimization techniques such as batching, caching, quantization, model distillation, prompt optimization, fallback routing, and use of smaller models where appropriate.</li><li>
Experience working with model-serving systems such as vLLM, Triton, TGI, SageMaker, Vertex AI, or custom inference services is preferred.</li><li>
Experience working with LLM and Multi-modal evaluation and benchmarking frameworks and domain‑specific benchmarks with the ability to interpret results and optimize model performance accordingly.</li></ul>
System Design &amp; Architecture<ul><li>
Preferred understanding of distributed systems, scaling patterns, and performance engineering</li><li>
Ability to design modular, maintainable, and efficient architectures</li><li>
Experience with API versioning, modularization, and designing long-running workflows</li><li>
Understanding of performance bottlenecks and low-latency backend patterns</li></ul>
Important information for candidates 
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:<ul><li>
Apply only through our official channels. We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/</li><li>
Verify the recruiter&rsquo;s identity. All our recruiters have verified LinkedIn profiles. If you&rsquo;re unsure, you can confirm their identity by checking their profile or contacting us through our website.</li><li>
Be cautious of unusual communication methods. We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.</li><li>
Double-check email addresses. All communication from us will come from emails ending in @tether.to or @tether.io</li><li>
We will never request payment or financial details. If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.</li></ul>
When in doubt, feel free to reach out through our official website.</div>

Machine Learning Systems Engineer

<div>Join Tether and Shape the Future of Digital Finance
At Tether, we&rsquo;re not just building products, we&rsquo;re pioneering a global financial revolution. Our cutting-edge solutions empower businesses&mdash;from exchanges and wallets to payment processors and ATMs&mdash;to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance: Our innovative product suite features the world&rsquo;s most trusted stablecoin, USDT, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that&rsquo;s just the beginning:
Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET, our flagship app that redefines secure and private data sharing.
Tether Education: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you&rsquo;re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We&rsquo;ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of our AI model team, you will drive innovation in model serving and inference architectures for advanced AI systems. Your work will focus on optimizing model deployment and inference strategies to deliver highly responsive, efficient, and scalable performance across real-world applications. You will work on a wide spectrum of systems, ranging from resource-efficient models designed for limited hardware environments to complex, multi-modal architectures that integrate data such as text, images, and audio.
We expect you to have deep expertise in designing and optimizing model serving pipelines and inference frameworks as well as a strong background in advanced model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel serving strategies and inference algorithms. Your responsibilities include engineering robust inference pipelines, establishing comprehensive performance metrics, and identifying and resolving bottlenecks in production environments. The ultimate goal is to enable high-throughput, low-latency, low-memory footprint, and scalable AI performance that delivers tangible value in dynamic, real-world scenarios.
Responsibilities
Break down the key responsibilities in bullet points. It&rsquo;s helpful to make them actionable and measurable. This could also be grouped into categories for more complex roles.<ul><li>
Design and deploy state-of-the-art model serving architectures that deliver high throughput and low latency while optimizing memory usage. Ensure these pipelines run efficiently across diverse environments, including resource-constrained devices and edge platforms. Establish clear performance targets such as reduced latency, improved token response, and minimized memory footprint.</li><li>
Build, run, and monitor controlled inference tests in both simulated and live production environments. Track key performance indicators such as response latency, throughput, memory consumption, and error rates, with special attention to metrics specific to resource-constrained devices. Document iterative results and compare outcomes against established benchmarks to validate performance across platforms.</li><li>
Identify and prepare high-quality test datasets and simulation scenarios tailored to real-world deployment challenges, specifically those encountered on low-resource devices. Set measurable criteria to ensure that these resources effectively evaluate model performance, latency, and memory utilization under various operational conditions.</li><li>
Analyze computational efficiency and diagnose bottlenecks in the serving pipeline by monitoring both processing and memory metrics. Address issues such as suboptimal batch processing, network delays, and high memory usage to optimize the serving infrastructure for scalability and reliability on resource-constrained systems.</li><li>
Work closely with cross-functional teams to integrate optimized serving and inference frameworks into production pipelines designed for edge and on-device applications. Define clear success metrics such as improved real-world performance, low error rates, robust scalability, optimal memory usage and ensure continuous monitoring and iterative refinements for sustained improvements.</li></ul><ul><li>
A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&amp;D (with good publications in A* conferences).</li><li>
Must have knowledge of Metal Shading Language (MSL). You should be comfortable writing custom compute shaders from scratch.</li><li>
Proven experience in low-level kernel optimizations and inference optimization on mobile devices is essential. Your contributions should have led to measurable improvements in inference latency, throughput, and memory footprint for domain-specific applications, particularly on resource-constrained devices and edge platforms.</li><li>
A deep understanding of modern model serving architectures and inference optimization techniques is required. This includes state-of-the-art methods for achieving low-latency, high-throughput performance, and efficient memory management in diverse, resource-constrained deployment scenarios.</li><li>
Must have strong expertise in writing GPU kernels for mobile devices (i.e., smartphones) as well as a deep understanding of model serving frameworks and engines. Practical experience in developing and deploying end-to-end inference pipelines, from optimizing models for efficient serving to integrating these solutions on resource-constrained devices is required.</li><li>
Demonstrated ability to apply empirical research to overcome challenges in model serving, such as latency optimization, computational bottlenecks, and memory constraints. You should be proficient in designing robust evaluation frameworks and iterating on optimization strategies to continuously push the boundaries of inference performance and system efficiency.</li><li>
Distributed Inference Systems: Designing and optimizing high-performance inference engines using techniques like Tensor Parallelism, Pipeline Parallelism, and Expert Parallelism to handle massive models on GPU clusters.</li><li>
Deep understanding of the math and structure behind Diffusion Models and Vision Transformers</li><li>
Understanding of Pruning, Quantization, Flash attention, KV Cache, Speculative Decoding (Eagle) etc.</li></ul>
Important information for candidates 
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:<ul><li>
Apply only through our official channels. We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/</li><li>
Verify the recruiter&rsquo;s identity. All our recruiters have verified LinkedIn profiles. If you&rsquo;re unsure, you can confirm their identity by checking their profile or contacting us through our website.</li><li>
Be cautious of unusual communication methods. We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.</li><li>
Double-check email addresses. All communication from us will come from emails ending in @tether.to or @tether.io</li><li>
We will never request payment or financial details. If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.</li></ul>
When in doubt, feel free to reach out through our official website.</div>

AI Research Engineer (Kernel & Inference Optimization) - 100% Remote Worldwide

<div>Join Tether and Shape the Future of Digital Finance
At Tether, we&rsquo;re not just building products, we&rsquo;re pioneering a global financial revolution. Our cutting-edge solutions empower businesses&mdash;from exchanges and wallets to payment processors and ATMs&mdash;to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance: Our innovative product suite features the world&rsquo;s most trusted stablecoin, USDT, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that&rsquo;s just the beginning:
Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET, our flagship app that redefines secure and private data sharing.
Tether Education: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you&rsquo;re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We&rsquo;ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of our AI research team, you will drive innovation in model compression and efficient deployment for advanced multimodal AI systems, including large language models (LLMs) and vision-language models (VLMs). Your work will focus on reducing model footprint and computational cost while preserving accuracy, enabling high-performance AI to run efficiently across resource-constrained edge devices. You will apply and advance compression techniques such as quantization, knowledge distillation, and pruning to streamline complex multimodal architectures that integrate text, images, and audio.
We expect you to have deep expertise in model compression methods and a strong background in multimodal model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel compression strategies that balance model size, latency, throughput, and accuracy. Your responsibilities include building robust compression pipelines, establishing performance and fidelity metrics, and addressing bottlenecks in production inference. The ultimate goal is to deliver scalable, low-memory, low-latency AI systems on edge devices (i.e., smartphones) that maintain high fidelity and tangible real-world value.
Responsibilities
Break down the key responsibilities in bullet points. It&rsquo;s helpful to make them actionable and measurable. This could also be grouped into categories for more complex roles.<ul><li>
Apply low-bit quantization to reduce model size and inference latency for generative AI models (LLMs, VLMs, multimodal) while maintaining accuracy and output quality.</li><li>
Leverage knowledge distillation to transfer capabilities from larger teacher models to smaller student models, enabling efficient multimodal reasoning across text, image, and audio inputs.</li><li>
Implement pruning techniques to remove redundant parameters and attention heads, reducing computational overhead without sacrificing task performance.</li><li>
Analyze trade-offs between model efficiency (size, latency, memory) and accuracy across quantization, distillation, and pruning methods; propose improvements based on empirical findings.</li><li>
Research and apply mixed-precision quantization and other advanced compression strategies (e.g., adaptive pruning schedules, distillation with intermediate feature matching) to optimize the accuracy&ndash;performance balance.</li><li>
Stay current with the latest research in model compression, including emerging techniques for multimodal and generative architectures.</li><li>
Document methodologies, experiments, and results clearly to support reproducibility, internal collaboration, and stakeholder communication.</li><li>
Author technical papers and publish findings in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, AAAI) to advance the field of model compression for multimodal AI.</li></ul> 
<ul><li>
A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&amp;D (with good publications in A* conferences).</li><li>
Experience with PyTorch deep learning frameworks or equivalent frameworks</li><li>
Hands-on experience with model quantization including both Quantization-Aware Training (QAT) and Post-Training Quantization (PTQ).</li><li>
Research and hands-on experience with knowledge distillation for compressing large models into smaller, efficient ones.</li><li>
Research and hands-on experience with model pruning for compressing large models into smaller, efficient ones.</li><li>
Solid understanding of neural network architectures and training processes &ndash; Including transformers (e.g., LLMs, VLMs), backpropagation, optimization, and fine-tuning techniques.</li><li>
Familiarity with C++ is a plus (especially for implementing low-level quantization kernels or inference optimizations).</li></ul>
Important information for candidates 
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:<ul><li>
Apply only through our official channels. We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/</li><li>
Verify the recruiter&rsquo;s identity. All our recruiters have verified LinkedIn profiles. If you&rsquo;re unsure, you can confirm their identity by checking their profile or contacting us through our website.</li><li>
Be cautious of unusual communication methods. We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.</li><li>
Double-check email addresses. All communication from us will come from emails ending in @tether.to or @tether.io</li><li>
We will never request payment or financial details. If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.</li></ul>
When in doubt, feel free to reach out through our official website.</div>

AI Research Engineer (Model Compression & Quantization)

<div>Join Tether and Shape the Future of Digital Finance
At Tether, we&rsquo;re not just building products, we&rsquo;re pioneering a global financial revolution. Our cutting-edge solutions empower businesses&mdash;from exchanges and wallets to payment processors and ATMs&mdash;to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance: Our innovative product suite features the world&rsquo;s most trusted stablecoin, USDT, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that&rsquo;s just the beginning:
Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET, our flagship app that redefines secure and private data sharing.
Tether Education: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you&rsquo;re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We&rsquo;ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of the AI model team, you will drive innovation in multi-modal reinforcement learning to advance next-generation intelligent systems. Your work will focus on optimizing decision-making and adaptive behavior across integrated data modalities such as text, images and audio to deliver enhanced intelligence, robust performance, and domain-specific capabilities for real-world challenges. You will develop and scale reinforcement learning techniques within complex multi-modal architectures, including diffusion-based generative models and autoregressive models for multimodal understanding, as well as resource-efficient models designed for constrained hardware environments. This includes conducting research on reinforcement learning algorithms for multimodal models, spanning diffusion models for image autoregressive models for multimodal reasoning, and unified multimodal frameworks.
You are expected to have deep expertise in designing multi-modal reinforcement learning systems and a strong background in advanced model architectures, with a hands-on, research-driven approach to building and deploying novel algorithms and training frameworks. You will design and develop RL infrastructure and reward modeling strategies to enable efficient large-scale training, improve training stability, and mitigate reward hacking and related failure modes. Your responsibilities also include curating multi-modal simulation environments and training datasets, improving baseline policy performance across modalities, and identifying and resolving bottlenecks in multi-modal learning and reward optimization. In addition, you will explore next-generation reinforcement learning paradigms that more directly and effectively learn from environment feedback, with the goal of unlocking superior, domain-adapted AI performance in dynamic, real-world environments.
Responsibilities<ul><li>
Conduct research on reinforcement learning algorithms for multimodal models, including diffusion-based approaches for image autoregressive models for multimodal understanding, and unified frameworks that integrate multiple modalities.</li><li>
Design and build reinforcement learning infrastructure that supports scalable, distributed training across multimodal systems while maintaining efficiency and reliability.</li><li>
Develop and refine reward modeling strategies that improve training stability, align model behavior with desired outcomes, and mitigate reward hacking and related failure modes.</li><li>
Create and curate multimodal simulation environments and datasets to support robust training, evaluation, and benchmarking of reinforcement learning systems.</li><li>
Design and conduct rigorous benchmarking and evaluation protocols to measure model performance, track progress against baselines, and validate improvements across multimodal tasks.</li><li>
Analyze and optimize policy performance across modalities by identifying bottlenecks in training, credit assignment, and cross-modal alignment.</li><li>
Investigate and develop next-generation reinforcement learning paradigms that more effectively learn from environment feedback, with the goal of achieving superior state-of-the-art (SOTA) performance.</li><li>
Publish research findings in top-tier conferences such as ICML, NeurIPS, ICLR, CVPR, ICCV, ECCV etc.</li></ul><ul><li>
A Master's degree in Computer Science or a related field is required; a PhD in Machine Learning, NLP, Computer Vision, or a closely related discipline is preferred, along with a strong track record of AI research and publications in top-tier conferences.</li><li>
Proven experience running large-scale reinforcement learning experiments in multimodal and vision-centric systems, including online RL settings, with demonstrated impact on domain-specific decision-making and measurable improvements in policy performance.</li><li>
Deep understanding of reinforcement learning algorithms and optimization methods applied to vision and multimodal learning problems, with a focus on improving policy stability, exploration, and sample efficiency in complex, high-dimensional environments involving images, video, and other modalities.</li><li>
Strong proficiency in PyTorch and deep learning frameworks for vision and multimodal AI, with hands-on experience building end-to-end RL pipelines covering simulation, training, evaluation, and deployment in production-grade systems.</li><li>
Demonstrated ability to apply empirical research to solve core RL challenges in multimodal and vision tasks, such as sample inefficiency, exploration-exploitation tradeoffs, and training instability, along with experience designing robust evaluation frameworks and iterating on algorithmic improvements to advance agent performance.</li><li>
Proven track record of research publications in top-tier conferences such as ICML, NeurIPS, ICLR, CVPR, ICCV, ECCV etc.</li></ul>
Important information for candidates 
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:<ul><li>
Apply only through our official channels. We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/</li><li>
Verify the recruiter&rsquo;s identity. All our recruiters have verified LinkedIn profiles. If you&rsquo;re unsure, you can confirm their identity by checking their profile or contacting us through our website.</li><li>
Be cautious of unusual communication methods. We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.</li><li>
Double-check email addresses. All communication from us will come from emails ending in @tether.to or @tether.io</li><li>
We will never request payment or financial details. If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.</li></ul>
When in doubt, feel free to reach out through our official website.</div>

AI Research Engineer (Multi-Modal Reinforcement Learning) - 100% Remote Worldwide

<div>Join Tether and Shape the Future of Digital Finance
At Tether, we&rsquo;re not just building products, we&rsquo;re pioneering a global financial revolution. Our cutting-edge solutions empower businesses&mdash;from exchanges and wallets to payment processors and ATMs&mdash;to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance: Our innovative product suite features the world&rsquo;s most trusted stablecoin, USDT, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that&rsquo;s just the beginning:
Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET, our flagship app that redefines secure and private data sharing.
Tether Education: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you&rsquo;re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We&rsquo;ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of our AI model team, you will drive innovation in model serving and inference architectures for advanced AI systems. Your work will focus on optimizing model deployment and inference strategies to deliver highly responsive, efficient, and scalable performance across real-world applications. You will work on a wide spectrum of systems, ranging from resource-efficient models designed for limited hardware environments to complex, multi-modal architectures that integrate data such as text, images, and audio.
We expect you to have deep expertise in designing and optimizing model serving pipelines and inference frameworks as well as a strong background in advanced model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel serving strategies and inference algorithms. Your responsibilities include engineering robust inference pipelines, establishing comprehensive performance metrics, and identifying and resolving bottlenecks in production environments. The ultimate goal is to enable high-throughput, low-latency, low-memory footprint, and scalable AI performance that delivers tangible value in dynamic, real-world scenarios.
Responsibilities<ul><li>
Design and deploy state-of-the-art model serving architectures that deliver high throughput and low latency while optimizing memory usage. Ensure these pipelines run efficiently across diverse environments, including resource-constrained devices and edge platforms. Establish clear performance targets such as reduced latency, improved token response, and minimized memory footprint.</li><li>
Build, run, and monitor controlled inference tests in both simulated and live production environments. Track key performance indicators such as response latency, throughput, memory consumption, and error rates, with special attention to metrics specific to resource-constrained devices. Document iterative results and compare outcomes against established benchmarks to validate performance across platforms.</li><li>
Identify and prepare high-quality test datasets and simulation scenarios tailored to real-world deployment challenges, specifically those encountered on low-resource devices. Set measurable criteria to ensure that these resources effectively evaluate model performance, latency, and memory utilization under various operational conditions.</li><li>
Analyze computational efficiency and diagnose bottlenecks in the serving pipeline by monitoring both processing and memory metrics. Address issues such as suboptimal batch processing, network delays, and high memory usage to optimize the serving infrastructure for scalability and reliability on resource-constrained systems.</li><li>
Work closely with cross-functional teams to integrate optimized serving and inference frameworks into production pipelines designed for edge and on-device applications. Define clear success metrics such as improved real-world performance, low error rates, robust scalability, optimal memory usage and ensure continuous monitoring and iterative refinements for sustained improvements.</li></ul><ul><li>
A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&amp;D (with good publications in A* conferences).</li><li>
Must have knowledge of Metal Shading Language (MSL). You should be comfortable writing custom compute shaders from scratch.</li><li>
Proven experience in low-level kernel optimizations and inference optimization on mobile devices is essential. Your contributions should have led to measurable improvements in inference latency, throughput, and memory footprint for domain-specific applications, particularly on resource-constrained devices and edge platforms.</li><li>
A deep understanding of modern model serving architectures and inference optimization techniques is required. This includes state-of-the-art methods for achieving low-latency, high-throughput performance, and efficient memory management in diverse, resource-constrained deployment scenarios.</li><li>
Must have strong expertise in writing GPU kernels for mobile devices (i.e., smartphones) as well as a deep understanding of model serving frameworks and engines. Practical experience in developing and deploying end-to-end inference pipelines, from optimizing models for efficient serving to integrating these solutions on resource-constrained devices is required.</li><li>
Demonstrated ability to apply empirical research to overcome challenges in model serving, such as latency optimization, computational bottlenecks, and memory constraints. You should be proficient in designing robust evaluation frameworks and iterating on optimization strategies to continuously push the boundaries of inference performance and system efficiency.</li><li>
Distributed Inference Systems: Designing and optimizing high-performance inference engines using techniques like Tensor Parallelism, Pipeline Parallelism, and Expert Parallelism to handle massive models on GPU clusters.</li><li>
Deep understanding of the math and structure behind Diffusion Models and Vision Transformers</li><li>
Understanding of Pruning, Quantization, Flash attention, KV Cache, Speculative Decoding (Eagle) etc.</li></ul>
Important information for candidates 
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:<ul><li>
Apply only through our official channels. We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/</li><li>
Verify the recruiter&rsquo;s identity. All our recruiters have verified LinkedIn profiles. If you&rsquo;re unsure, you can confirm their identity by checking their profile or contacting us through our website.</li><li>
Be cautious of unusual communication methods. We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.</li><li>
Double-check email addresses. All communication from us will come from emails ending in @tether.to or @tether.io</li><li>
We will never request payment or financial details. If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.</li></ul>
When in doubt, feel free to reach out through our official website.</div>

AI Research Engineer (Model Compression & Quantization) - 100% Remote Worldwide

<div>Join Tether and Shape the Future of Digital Finance
At Tether, we&rsquo;re not just building products, we&rsquo;re pioneering a global financial revolution. Our cutting-edge solutions empower businesses&mdash;from exchanges and wallets to payment processors and ATMs&mdash;to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.
Innovate with Tether
Tether Finance: Our innovative product suite features the world&rsquo;s most trusted stablecoin, USDT, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that&rsquo;s just the beginning:
Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.
Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET, our flagship app that redefines secure and private data sharing.
Tether Education: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.
Tether Evolution: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.
Why Join Us?
Our team is a global talent powerhouse, working remotely from every corner of the world. If you&rsquo;re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We&rsquo;ve grown fast, stayed lean, and secured our place as a leader in the industry.
If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.
Are you ready to be part of the future?
About the job
As a member of the AI model team, you will drive innovation in training and optimizing vision-language models with a focus on real-world deployment. Your work will span the full model development lifecycle - from data curation and training pipeline design to model evaluation and optimization - with the goal of building models that are both highly capable and practical to deploy at scale.
You will work across a wide spectrum of multimodal architectures integrating text and vision, applying state-of-the-art research to improve model quality, efficiency, and domain-specific performance. We expect you to bring a research-driven mindset combined with strong engineering discipline - someone who can identify the right technique for a given problem, implement it rigorously, and measure its impact clearly.
You will work closely with a small, high-caliber team where your contributions will have direct and meaningful impact. If you are passionate about pushing the boundaries of what multimodal AI can achieve in production environments, this is your opportunity.
Responsibilities<ul><li>
Conduct end-to-end research and engineering on vision-language models, covering training, evaluation, and optimization across the full model development lifecycle.</li><li>
Design and implement post-training pipelines including supervised fine-tuning, knowledge distillation, and reinforcement learning from human feedback.</li><li>
Develop and maintain high-quality multimodal datasets, including data curation, filtering, and balancing for domain-specific tasks.</li><li>
Drive model efficiency and deployability, adapting models for resource-constrained environments using compression and optimization techniques.</li><li>
Design and implement evaluation frameworks and benchmarks to measure model performance, robustness, and real-world task success.</li><li>
Build and scale training workflows across distributed GPU infrastructure.</li><li>
Identify and resolve bottlenecks in training pipelines to achieve state-of-the-art model quality on target benchmarks.</li><li>
Contribute to and leverage open-source ecosystems including models, datasets, and tooling to accelerate development.</li><li>
Stay current with the latest research in multimodal learning and vision-language systems, translating relevant findings into practical improvements.</li><li>
Publish research findings in top-tier AI conferences and journals where applicable.</li></ul><ul><li>
Degree in Computer Science, Machine Learning, or a related field; MS/PhD preferred.</li><li>
Strong experience with multimodal post-training workflows including supervised fine-tuning, knowledge distillation, and reinforcement learning from feedback.</li><li>
Hands-on experience with parameter-efficient fine-tuning and distributed training frameworks.</li><li>
Demonstrated ability to build and improve vision-language models with measurable results on standard benchmarks or real-world tasks.</li><li>
Experience adapting models for resource-constrained environments.</li><li>
Proven open-source contributions in multimodal AI on GitHub or HuggingFace.</li><li>
Publications at top AI conferences (NeurIPS, ICML, ICLR, CVPR, ECCV etc.)</li></ul>
Important information for candidates 
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:<ul><li>
Apply only through our official channels. We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page: https://tether.recruitee.com/</li><li>
Verify the recruiter&rsquo;s identity. All our recruiters have verified LinkedIn profiles. If you&rsquo;re unsure, you can confirm their identity by checking their profile or contacting us through our website.</li><li>
Be cautious of unusual communication methods. We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.</li><li>
Double-check email addresses. All communication from us will come from emails ending in @tether.to or @tether.io</li><li>
We will never request payment or financial details. If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.</li></ul>
When in doubt, feel free to reach out through our official website.</div>

AI Research Engineer (Multi-Modal & Vision) - 100% Remote Worldwide

Join Tether Operations Limited and explore 10   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.