project engineer

electrical engineer

planning engineer

qa/qc engineer

electrical design engineer

machine learning engineer

MultiBank Group

<div>Welcome to MultiBank Group, a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.
Join our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US$ 35 billion. As a heavily regulated institution with oversight from 18+ financial regulators across 5 continents, and recipient of over 80 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.
Role Overview
We are seeking a Senior Machine Learning Engineer to join our AI team as a technical owner of ML products and infrastructure. This is a deeply hands-on engineering position for someone who builds and scales production AI systems used by real users in real-time environments. The right candidate operates across the full ML lifecycle &mdash; from model design through deployment, optimization, and ongoing performance in production &mdash; and contributes to the technical direction of the AI platform.
Key Responsibilities<ul><li>
Architect and implement robust ML systems in production environments, ensuring scalability, reliability, and performance from day one</li><li>
Build and deploy supervised, unsupervised, deep learning, and generative AI models into live production environments at scale</li><li>
Own technical design for ML pipelines, feature stores, training infrastructure, and inference systems, driving decisions that balance performance, cost, and maintainability</li><li>
Design and deliver RAG systems, fine-tuning pipelines, prompt engineering frameworks, and evaluation pipelines for production-grade LLM applications</li><li>
Implement and maintain CI/CD for ML, model versioning, monitoring, drift detection, and automated retraining pipelines</li><li>
Continuously optimize model performance, inference latency, cost efficiency, and reliability across live systems</li><li>
Collaborate with product managers, engineers, and data teams to translate business problems into scalable, maintainable AI solutions</li><li>
Mentor junior and mid-level ML engineers, establish best practices, and contribute to technical standards across the team</li><li>
Contribute to strategic decisions around data architecture, AI infrastructure, and cloud platform direction</li><li>
Work with mobile attribution and customer engagement data sources including Adjust, MoEngage, and Firebase for ML use cases such as churn prediction, personalization, and campaign optimization</li></ul>
Requirements<ul><li>
7 to 15 or more years of experience in software engineering, data science, or ML engineering</li><li>
Strong background in product companies, scale-ups, or enterprise AI platforms</li><li>
Proven track record of building production-grade AI systems, not solely notebooks or proof-of-concept work</li><li>
Comfortable owning systems end-to-end from data through model through deployment through monitoring</li><li>
Product-first engineering approach, not research-only profiles</li><li>
Advanced Python engineering skills with strong systems thinking and a focus on production quality</li><li>
Comfortable with fast iteration cycles and deploying models into live environments</li><li>
Ability to work directly and confidently with stakeholders and product owners</li><li>
Fintech or financial services experience is an advantage</li></ul>
Technical Skills
Machine Learning and AI: PyTorch, TensorFlow, XGBoost, LightGBM, Hugging Face (Transformers, Datasets, Diffusers)
LLM and GenAI: OpenAI and Anthropic APIs, LangChain, LlamaIndex; RAG architectures with vector DB and retrieval pipelines; embedding models (OpenAI, Cohere, open-source); Pinecone, Weaviate, Milvus, FAISS; fine-tuning via LoRA and PEFT frameworks; evaluation using RAGAS and custom pipelines
MLOps and Production: Docker, Kubernetes, MLflow, Weights and Biases, Airflow, Dagster, Prefect, GitHub Actions, GitLab CI, Evidently AI, Arize, custom observability stacks
Cloud: AWS (SageMaker, EKS, S3, Lambda), Azure ML, Azure Databricks, GCP
Data Stack: Databricks, Spark, PySpark, Delta Lake, Apache Iceberg, Lakehouse architectures
Why Join Us?<ul><li>
Work with one of the world&rsquo;s leading financial derivatives institutions.</li><li>
Competitive salary plus performance-based incentives.</li><li>
Access to a dynamic, international, and fast-growing environment.</li><li>
Strong opportunities for career progression within a global financial group.</li><li>
Be part of a business committed to innovation, excellence, and long-term growth.</li></ul>
Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.
MultiBank Group is an equal opportunity employer. We welcome applications from candidates of all backgrounds and do not discriminate on the basis of nationality, gender, age, religion, or disability.</div>

Senior Machine Learning Engineer

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
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

Almaimana Accounting and Bookkeeping

Location: Remote / Dubai, UAE (Project-Based) Employment Type: Freelance / Contract Department: Technology &amp; Digital InnovationJob SummaryWe are seeking a talented and experienced Freelance AI Engineer to design, develop, and implement Artificial Intelligence (AI) solutions on a project basis. The ideal candidate will have hands-on experience in Machine Learning, Generative AI, Natural Language Processing (NLP), AI automation, and Large Language Models (LLMs). The role requires the ability to work independently, manage project timelines, and deliver scalable AI solutions aligned with business objectives.Key Responsibilities<ul><li>Develop and deploy AI-powered applications, chatbots, virtual assistants, and automation solutions.</li><li>Build and fine-tune Machine Learning and Deep Learning models.</li><li>Design and implement Generative AI solutions using Large Language Models (LLMs).</li><li>Integrate AI solutions with websites, mobile applications, ERP systems, and business platforms.</li><li>Develop Retrieval-Augmented Generation (RAG) systems and AI agents.</li><li>Analyze business requirements and recommend suitable AI technologies.</li><li>Prepare technical documentation and deployment guides.</li><li>Conduct testing, troubleshooting, and optimization of AI applications.</li><li>Ensure data security, privacy, and compliance with industry best practices.</li><li>Provide post-deployment support and maintenance when required.</li></ul>Required Qualifications<ul><li>Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or related field (preferred).</li><li>Proven experience in AI/ML development and deployment.</li><li>Strong proficiency in Python and AI development frameworks.</li><li>Experience with Generative AI platforms and APIs.</li><li>Knowledge of NLP, Machine Learning, and Deep Learning techniques.</li><li>Experience integrating AI solutions through APIs and cloud services.</li><li>Strong problem-solving and communication skills.</li><li>Ability to work independently and meet project deadlines.</li></ul>Technical Skills<ul><li>Python</li><li>TensorFlow, PyTorch, Scikit-learn</li><li>OpenAI, Gemini, Claude, or similar AI platforms</li><li>LangChain, LlamaIndex</li><li>RAG Architecture and AI Agents</li><li>SQL and NoSQL Databases</li><li>Vector Databases (Pinecone, ChromaDB, Weaviate)</li><li>REST APIs</li><li>Docker and Cloud Platforms (AWS, Azure, GCP)</li><li>Git Version Control</li></ul>Preferred Experience<ul><li>AI Chatbot Development</li><li>Intelligent Document Processing (IDP)</li><li>OCR and Computer Vision Applications</li><li>Business Process Automation</li><li>Predictive Analytics and Data Science Projects</li><li>MLOps and Model Deployment</li></ul>DeliverablesThe selected freelancer may be required to:<ul><li>Develop custom AI applications.</li><li>Create AI-powered customer support solutions.</li><li>Automate business processes using AI.</li><li>Build intelligent document management systems.</li><li>Integrate AI models with existing software platforms.</li><li>Provide training and knowledge transfer to internal teams.</li></ul>Contract Terms<ul><li>Project-based or hourly engagement.</li><li>Flexible working hours.</li><li>Remote work arrangement.</li><li>Payment based on agreed milestones and deliverables.</li><li>Opportunity for long-term collaboration on future AI projects.</li></ul>How to ApplyInterested candidates should submit:<ul><li>Updated CV/Resume</li><li>Portfolio of AI projects</li><li>GitHub or relevant technical profiles</li></ul>Only candidates with demonstrated experience in AI development and successful project delivery will be considered.Application Question(s):<ul><li>What is your expected Salary?</li><li>Can you join immediately after selection?</li></ul>Education:<ul><li>Bachelor's (Preferred)</li></ul>Work Location: In person

Freelance AI Engineer

Ezra

<div>Predictive Analyst 


Location: Dubai, United Arab Emirates or Nairobi, Kenya

Reports to: Director of Prediction &amp; Data 

<h3 class="jobSectionHeader">
About the role:</h3>

We are seeking an experienced Data / Decision Scientist to join our team. As a Predictive Analyst, you will be working with and enhancing our prediction pipelines code base, to enable prediction at scale across our many jurisdictions and within EZRA's array of credit products (term and revolving), and to drive new and existing business performance - specifically focused on balancing revenue and bad debt, i.e. net revenue optimisation.

You will be responsible for designing and developing tools to enable fast model development, conducting experiments, and developing data-driven solutions to solve complex problems.

The ideal candidate should have strong analytical and problem-solving skills, in addition to high proficiency in Python and SQL, with experience in developing machine learning systems utilizing software engineering principles.

Previous experience in fintech, specifically credit decisioning systems, airtime credit services or mobile money lending leveraging alternate data is further advantageous. 

<h3 class="jobSectionHeader">
Key responsibilities:</h3>
<ul><li>Data Strategy &amp; Preparation: Review and identify key datasets from partners to develop robust ML models. Collect, preprocess, and analyze large, complex datasets to ensure data integrity.</li>
<li>Feature Engineering: Define features and perform advanced clustering, feature reduction, and selection techniques.</li>
<li>Model Development: Build predictive models to improve partner and product performance, developing specific &quot;Ezra Prediction&quot; modules in Python for automated ML systems.</li>
<li>Experimental Design: Design and conduct experiments (A/B testing) to validate models and hypotheses, enhancing overall market understanding.</li>
<li>Deployment &amp; Collaboration: Partner with cross-functional teams to implement and deploy machine learning solutions into production environments.</li>
<li>Insight Communication: Translate complex findings into actionable insights for both technical and non-technical stakeholders through reports and visualizations.</li>
<li>Optimization: Continuously monitor and iterate on model performance, prediction systems, and underlying algorithms.</li></ul> 

<h3 class="jobSectionHeader">
Essential Qualifications and Experience:</h3>
<ul><li>Education: Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field.</li>
<li>Professional Experience: 5+ years of experience in a Data / Decision Science or Machine Learning Engineering role with a proven track record.</li>
<li>Technical Proficiency:</li>
<li><ul><li>Expert-level Python programming skills.</li>
<li>Advanced SQL skills (Postgres, Redshift, or similar).</li>
<li>Deep understanding of data structures (lists, dictionaries, arrays, data frames).</li>
<li>Data visualization / analysis / statistical inference.</li>
</ul></li><li>Core Competencies: Strong analytical and problem-solving skills, with the ability to work effectively both independently and within a team.</li>
<li>Communication: Exceptional story-telling and presentation skills, specifically the ability to bridge the gap between technical complexity and business logic.</li>
</ul><h3 class="jobSectionHeader">Beneficial Qualifications and Experience:</h3>
<ul><li>MLOps &amp; Production: Experience operationalizing ML models into production with measurable impact on product and financial optimization.</li>
<li>DevOps Tools: Proficiency with Source Control Management (Git/Bitbucket) and CI/CD pipelines (e.g., Jenkins).</li>
<li>Architecture: Understanding of Feature Store architecture and implementation.</li>
<li>Environment: Experience working in Linux OS variants (Debian) and comfort utilizing the command line.</li>
<li>Agility: Ability to balance &quot;start-up&quot; stage project work with the development of long-term scalable ML modules.</li>
<li>Language Skills: Proficiency in French is beneficial to support operations across various jurisdictions.</li>
</ul><h3 class="jobSectionHeader">The Ideal Candidate:</h3>
<ul><li>Innovation-Driven: Passionate about deploying customer-centric products that exceed quality and delivery expectations.</li>
<li>Growth Mindset: Proud of their work but driven by continuous improvement; able to self-critique and accept constructive feedback.</li>
<li>Detail-Oriented: High attention to detail with a commitment to process, procedure, and documentation as pillars of excellence.</li>
<li>Adaptable: Comfortable stepping outside of their comfort zone to learn new tasks and technologies.</li>
</ul><h3 class="jobSectionHeader">Company overview:</h3>

Ezra provides B2B digital lending solutions for emerging markets in partnership with mobile and digital wallet operators and financial service providers. Ezra supports 24 operations in 23 countries, across Africa, the Middle East and Asia. Our key office locations are in Nairobi, Kenya and Dubai, UAE.

Our flagship products are Airtime Credit Services (ACS), Nano and BNPL.
<ul>
<li>ACS is an airtime or data advance offered to prepaid mobile subscribers at the point of low credit.</li>
<li>Nano is a micro cash advance offered to mobile wallet users on demand.</li>
<li>BNPL facilitates payment installments for products and services</li></ul> 


As a FinTech company, our business is entirely technology and data driven, from determining subscriber eligibility, generating relevant offers, managing risk, loan issuance, recovery, optimizing performance and reporting, reconciliation and billing. 


Each day we process approximately 21M loan requests and 1.4 TB of data across our markets. This process needs to be robust, reliable and secure. 


But it doesn't end there. We're exploring new ways of using our platform and transactional data to improve our products and develop new product opportunities.</div>

Predictive Analyst

sandan AI

<div>Location: Berlin / Remote (DACH time zone) 
Employment Type: Full-time, permanent 
Start Date: Immediate 
Language: Native-level English proficiency (C1-C2 level, German a bonus)

_____________________

ABOUT US

sandan AI is a Berlin-based AI-native startup serving enterprise customers across the DACH region. We are shaping what marketing looks like in an agentic economy &mdash; and building the platform on which this new generation of marketing workflows runs.

Our ambition is to build software the way software should be built in 2026: agentic, iterative, and with AI as an integral part of the engineering workflow.

HOW WE WORK

We use code harnesses such as Claude Code and Codex not as gimmicks, but as a core part of our development process. Our engineers work daily with agentic coding workflows &mdash; from architecture sketches and implementation to refactoring and testing.

People joining us either already work productively with these tools or bring the clear motivation to learn and master them quickly and deeply.
<h2 class="jobSectionHeader">
Tasks</h2>
<ul><li>Develop and maintain our full-stack applications within the modern JavaScript/TypeScript ecosystem</li>
<li>Design and implement scalable backend services using Node.js and Nest.js</li>
<li>Build high-performance frontend solutions with React.js and Next.js</li>
<li>Design and optimize relational databases (PostgreSQL, MySQL, MS SQL)</li>
<li>Containerize and orchestrate services using Docker and Kubernetes</li>
<li>Develop and integrate REST APIs</li>
<li>Build and operate data pipelines, feature stores, and ML workflows for our agentic systems</li>
<li>Develop, train, and evaluate machine learning models for marketing use cases (attribution, targeting, forecasting, anomaly detection)</li>
<li>Implement Retrieval-Augmented Generation (RAG) pipelines (embeddings, vector stores, re-ranking)</li>
<li>Set up and maintain LLM evaluation frameworks, prompt optimization workflows, and systematic quality benchmarks</li>
<li>Apply code harnesses (especially Claude Code and Codex) throughout the daily development process &mdash; from planning and implementation to code review</li>
<li>Collaborate closely with the founding team on the product architecture of agentic systems</li>
</ul><h2 class="jobSectionHeader">Requirements</h2>

Core Technical Competencies (Engineering)
<ul>
<li>Several years of professional experience in full-stack development</li>
<li>Strong knowledge of TypeScript and JavaScript</li>
<li>Confident working with React.js, Next.js, Node.js, and Nest.js</li>
<li>Experience with relational databases (PostgreSQL, MySQL, MS SQL)</li>
<li>Hands-on experience with container technologies (Docker, Kubernetes)</li>
<li>Familiarity with REST API design and Git workflows</li>
</ul>
Data Science &amp; Machine Learning
<ul>
<li>Solid Python skills, including common data/ML stacks (pandas, NumPy, scikit-learn, PyTorch, or TensorFlow)</li>
<li>Experience across the end-to-end lifecycle of ML models: data preparation, feature engineering, training, validation, deployment, and monitoring</li>
<li>Strong understanding of statistical fundamentals (hypothesis testing, regression, classification, time series)</li>
<li>Experience with modern LLM workflows: prompt engineering, RAG, embeddings, vector databases (e.g. Pinecone, Weaviate, pgvector)</li>
<li>Hands-on experience in model evaluation: metrics, benchmarks, A/B testing, and systematic evaluation frameworks</li>
<li>Experience with notebook-based exploration environments (Jupyter, Colab) and transitioning them into production-ready pipelines</li>
<li>Familiarity with MLOps tools (e.g. MLflow, Weights &amp; Biases, DVC) is a plus</li>
</ul>
Code Harnesses
<ul>
<li>Experience with Claude Code and/or Codex is highly appreciated &mdash; otherwise, a strong willingness to actively learn and adopt these tools</li>
</ul>
Personal Qualifications
<ul>
<li>Excellent German (C2) and English skills (minimum C1)</li>
<li>Genuine interest in generative AI and agentic systems</li>
<li>Builder mentality: you deliver production-grade software, not just prototypes</li>
<li>Analytical mindset: you make data-driven decisions and critically evaluate model behavior</li>
</ul>
Nice to have
<ul>
<li>A defining role in an AI-native startup with a strong enterprise focus</li>
<li>Competitive salary and employee stock ownership plan (ESOP)</li>
<li>Fully funded access to all relevant code harnesses, LLM APIs, and developer tools (Claude Max, Codex, GitHub Copilot, etc.)</li>
<li>Compute budget for experiments, model training, and ML workloads</li>
<li>Modern hardware setup (MacBook Pro of your choice)</li>
<li>Flexible working hours and remote work options</li>
<li>Office in Berlin and location in Dubai (DIFC AI Campus)</li>
<li>A steep learning curve in Agentic AI, LLM orchestration, and AI-native engineering</li>
</ul><h2 class="jobSectionHeader">Benefits</h2>
<ul><li>A defining role in an AI-native startup with a strong enterprise focus</li>
<li>Competitive salary and employee stock ownership plan (ESOP)</li>
<li>Fully funded access to all relevant code harnesses, LLM APIs, and developer tools (Claude Max, Codex, GitHub Copilot, etc.)</li>
<li>Compute budget for experiments, model training, and ML workloads</li>
<li>Modern hardware setup (MacBook Pro of your choice)</li>
<li>Flexible working hours and remote work options</li>
<li>Office in Berlin and location in Dubai (DIFC AI Campus)</li>
<li>A steep learning curve in Agentic AI, LLM orchestration, and AI-native engineering</li>
</ul>
We look forward to receiving your application, including your CV and &mdash; if available &mdash; a GitHub or portfolio link.

Please also let us know your earliest possible start date.

Bonus: Tell us in two or three sentences about the most recent ML project you worked on &mdash; and how you currently use Claude Code, Codex, or comparable tools in your workflow.</div>

Senior Full-Stack Developer / AI Engineer / Data Scientist (m/w/d)

Dataiku

<div>
 Dataiku is the Platform for AI Success, the enterprise orchestration layer for building, deploying, and governing AI. In a single environment, teams design and operate analytics, machine learning, and AI agents with the transparency, collaboration, and control enterprises require. Sitting above data platforms, cloud infrastructure, and AI services, Dataiku connects the full enterprise AI stack &mdash; empowering organizations to run AI across multi-vendor environments with centralized governance.
 
 
 The world&rsquo;s leading companies rely on Dataiku to operationalize AI and run it as a true business performance engine delivering measurable value. For more, visit the Dataiku blog, LinkedIn, X, and YouTube.
 
 
 The role of a Data Scientist at Dataiku is quite unique. Our Data Scientists not only code up solutions to real-world problems, but also participate in client-facing endeavours throughout the customer journey. This includes supporting their discovery of the platform, helping integrate Dataiku with other tools and technologies, some user training, and co-developing data science projects from design to deployment.
 
 
 Just as non-technical skills are important, so too are technical skills. Our Data Scientists work on the Dataiku platform every day. Aside from the visual tools, our team primarily uses Python and SQL, with occasional work in other languages (e.g., R, PySpark, JavaScript). An ideal candidate is excited to learn complex new technologies and modelling techniques while being able to explain their work to other data scientists and clients.
 
 
 
 In This Role, You'll Help The Team
 
 
 
 <ul>
 <li>
 Co-develop production-level data science projects with our customers
 </li>
 <li>
 Analyse and investigate various kinds of data and machine learning applications across industries and use cases
 </li>
 <li>
 Help users discover and master the Dataiku platform, via user trainings, office hours, and ongoing consultative support
 </li>
 <li>
 Provide data science expertise both to customers and internally to Dataiku&rsquo;s sales and marketing teams
 </li>
 <li>
 Develop custom Python-based &ldquo;plugins&rdquo; in collaboration with Solutions, R&amp;D, and Product teams, to enhance Dataiku&rsquo;s functionality
 
 
 </li>
 </ul>
 
 You might be a good fit for the role if you have:
 
 
 
 <ul>
 <li>
 English - fluent, Arabics - fluent/native will be a big plus
 </li>
 <li>
 Curiosity and a desire to learn new topics and skills
 </li>
 <li>
 Empathy for others and an eagerness to share your knowledge and expertise with your colleagues, Dataiku&rsquo;s customers, and the general public
 </li>
 <li>
 The ability to clearly explain complex topics to technical as well as non-technical audiences
 </li>
 <li>
 2 - 10 years of experience with Python and SQL
 </li>
 <li>
 2 - 10 years of experience with building ML models and using ML tools (e.g., sklearn)
 </li>
 <li>
 Familiarity with data visualisation in Python and R
 </li>
 <li>
 Understanding of underlying data systems such as Cloud architectures, Hadoop, or SQL
 
 
 </li>
 </ul>
 
 Technical Skills That May Help You In The Role
 
 
 
 <ul>
 <li>
 Experience with Consulting and/or Customer-facing Data Science roles
 </li>
 <li>
 Experience with Data Engineering or MLOps
 </li>
 <li>
 Experience developing WebApps in JavaScript, RShiny, or Dash
 </li>
 <li>
 Experience building APIs
 </li>
 <li>
 Experience using enterprise data science tools
 </li>
 <li>
 Passion for teaching or public speaking
 
 
 </li>
 </ul>
 
 What are you waiting for!
 
 
 
 At Dataiku, you'll be part of a journey to shape the ever-evolving world of AI. We're not just building a product; we're crafting the future of AI. If you're ready to make a significant impact in a company that values innovation, collaboration, and your personal growth, we can't wait to welcome you to Dataiku! And if you&rsquo;d like to learn even more about working here, you can visit our Dataiku LinkedIn page.
 
 
 
 Our practices are rooted in the idea that everyone should be treated with dignity, decency and fairness. Dataiku also believes that a diverse identity is a source of strength and allows us to optimize across the many dimensions that are needed for our success. Therefore, we are proud to be an equal opportunity employer. All employment practices are based on business needs, without regard to race, ethnicity, gender identity or expression, sexual orientation, religion, age, neurodiversity, disability status, citizenship, veteran status or any other aspect which makes an individual unique or protected by laws and regulations in the locations where we operate. This applies to all policies and procedures related to recruitment and hiring, compensation, benefits, performance, promotion and termination and all other conditions and terms of employment. If you need assistance or an accommodation, please contact us at:
 
 reasonable-accommodations@dataiku.com
 
 
 
 Protect yourself from fraudulent recruitment activity
 
 
 
 
 Dataiku will never ask you for payment of any type during the interview or hiring process. Other than our video-conference application, Zoom, we will also never ask you to make purchases or download third-party applications during the process. If you experience something out of the ordinary or suspect fraudulent activity, please review our page on identifying and reporting fraudulent activity here.
 
 
 
</div>

Senior Data Scientist

<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

Explore 532+ Machine learning engineer in Dubai this June. Find roles across top companies and apply now to boost your career.