civil engineer

electrical engineer

planning engineer

project engineer

it support engineer

intelligence engineer

STAMN Real Estate Development LLC

We are seeking a skilled IT Engineer who is fluent in Chinese and English, with strong expertise in Artificial Intelligence (AI) and CRM system implementation. The ideal candidate will be responsible for designing, implementing, and maintaining AI-driven solutions and CRM platforms to support business operations and enhance customer engagement.Key Responsibilities:<ul><li>Design, develop, and implement AI-based solutions to improve business efficiency and decision-making.</li><li>Lead the implementation, customization, and integration of CRM systems.</li><li>Collaborate with internal teams to gather system requirements and translate them into technical solutions.</li><li>Manage system upgrades, troubleshooting, and ongoing maintenance of IT infrastructure and applications.</li><li>Analyze data and workflows to recommend automation and AI-driven improvements.</li><li>Ensure data security, system performance, and compliance with IT policies.</li><li>Provide technical support and training to users on CRM and AI tools.</li><li>Liaise with Chinese-speaking stakeholders, vendors, and partners for project coordination.</li><li>Act as the primary point of contact between the company and CRM vendors, ensuring clear communication and smooth project execution.</li><li>Analyze and understand key CRM functionalities and align them with business requirements.</li><li>Oversee the implementation of CRM solutions within the company&rsquo;s systems, ensuring proper integration and performance.</li><li>Identify gaps and recommend practical solutions to optimize system usage and business processes.</li><li>Prepare and present reports, insights, and technical recommendations to management for informed decision-making.</li></ul>Requirements:<ul><li>Bachelor&rsquo;s degree in Information Technology, Computer Science, or a related field.</li><li>Proven experience in AI technologies (Machine Learning, NLP, automation tools).</li><li>Hands-on experience with CRM implementation and integration.</li><li>Strong programming knowledge (Python, Java, or similar).</li><li>Experience with cloud platforms (AWS, Azure, or Google Cloud) is an advantage.</li><li>Fluency in Chinese (Mandarin) and English is mandatory.</li><li>Strong problem-solving and analytical skills.</li><li>Excellent communication and project management abilities.</li></ul>Preferred Qualifications:<ul><li>Experience in real estate, construction, or corporate environments in the UAE.</li><li>Certification in AI, Data Science, or CRM platforms.</li><li>Knowledge of data analytics and business intelligence tools.</li></ul>Work Location: In person

IT Engineer (Chinese Speaker – AI & CRM Specialist)

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 an AI Engineer to design, build, and deploy intelligent AI agents and automated workflows that address real business problems. This is a hands-on, high-impact role within the Artificial Intelligence and Advanced Analytics team. The successful candidate will own end-to-end delivery of AI agents from scoping and architecture through integration, testing, and production deployment, enabling the organization to automate complex processes and unlock value from generative AI.
Key Responsibilities<ul><li>
Design, build, and deploy AI agents using frontier LLMs including Claude (Anthropic API), OpenAI, Gemini, and other frontier models</li><li>
Architect multi-agent systems and agentic workflows using frameworks including LangChain, LangGraph, CrewAI, AutoGen, and Semantic Kernel</li><li>
Build and manage automated business workflows using n8n, Make (Integromat), Zapier, and custom API integrations</li><li>
Implement RAG pipelines with vector databases including Pinecone, Weaviate, Qdrant, and pgvector to give agents access to organizational knowledge bases</li><li>
Design tool-use and function-calling integrations, connecting agents to internal systems, APIs, databases, and third-party services</li><li>
Fine-tune and prompt-engineer LLMs to optimize agent behavior, reliability, and task accuracy</li><li>
Collaborate with business stakeholders to identify automation opportunities and translate requirements into agent-based solutions</li><li>
Monitor, evaluate, and continuously improve deployed agents across quality, latency, cost, and safety metrics</li><li>
Establish and maintain best practices for agent safety, guardrails, human-in-the-loop controls, and responsible AI deployment</li><li>
Develop MCP (Model Context Protocol) server integrations to extend agent capabilities</li></ul>
Requirements<ul><li>
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field; equivalent practical experience will be considered</li><li>
2 or more years of hands-on experience building production AI systems or intelligent automation solutions</li><li>
Demonstrated experience building agents or workflows with LangChain, LangGraph, CrewAI, n8n, or comparable frameworks</li><li>
Proven ability to integrate LLM APIs including Anthropic Claude and OpenAI into real-world applications</li><li>
Experience with vector databases and semantic search implementations is strongly preferred</li><li>
Portfolio or demonstrable projects showing deployed agents, automation workflows, or RAG-based applications</li><li>
Proficiency in Python as the primary language; JavaScript or TypeScript is beneficial</li><li>
Familiarity with cloud platforms, Docker, FastAPI, and CI/CD practices for AI pipelines</li></ul>
Technical Skills
LLM APIs: Anthropic Claude (claude-opus-4, claude-sonnet-4), OpenAI GPT-4o, Google Gemini, Mistral
Agent Frameworks: LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, Haystack
Workflow Automation: n8n, Make (Integromat), Zapier, Apache Airflow
Vector Databases and RAG: Pinecone, Weaviate, Qdrant, pgvector, Chroma, LlamaIndex
Programming: Python (primary), JavaScript/TypeScript, REST API design
Cloud and MLOps: AWS, Azure, GCP, Docker, FastAPI, CI/CD for AI pipelines
Observability and Evaluation: LangSmith, Helicone, Weights and Biases, custom evaluation harnesses
AI Agent Focus Areas<ul><li>
Autonomous and semi-autonomous agents for customer service, operations, marketing, and data analysis</li><li>
Multi-agent orchestration including planner, executor, critic, and memory agent patterns</li><li>
Knowledge retrieval systems including enterprise RAG, document Q&amp;A, and semantic search</li><li>
Process automation integrating CRM, ERP, and communication tools end-to-end</li><li>
Agent safety, guardrails, and human-in-the-loop oversight mechanisms</li><li>
MCP server development for extending agent capabilities</li></ul>
Soft Skills<ul><li>
Strong problem-solving ability and analytical thinking</li><li>
Ability to translate complex business needs into practical technical solutions</li><li>
Effective collaboration and communication in a team-oriented environment</li><li>
Intellectual curiosity and commitment to staying current with AI research and trends</li></ul>
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>

AI Engineer – Generative AI and Automation

Dyson

<div>
 
 About Us
 
 
 
 At Dyson, we&rsquo;re driven by a relentless pursuit of innovation&mdash;pushing boundaries in engineering, AI, and robotics. Our new Data Intelligence team sits at the heart of this mission: shaping Dyson&rsquo;s future through data. Here, we blend creativity, precision, and audacity to power intelligent products. We craft data strategies and pipelines that fuel the next generation of connected devices.
 
 
 You&rsquo;ll work alongside brilliant minds from Dyson global engineering team and external software/hardware partners in an environment built for exploration, discovery, delivery and impact.
 
 
 
 About The Role
 
 
 
 We are looking for a specialized Lead Data Intelligence Machine Learning Engineer to design and implement in-house tools that automate our data labelling pipelines. Your primary goal will be to reduce our reliance on manual annotation by leveraging techniques like Active Learning, Weak Supervision, and Synthetic Data Generation. You will bridge the gap between raw data collection and model-ready datasets, ensuring high-quality labels at scale.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Architect Labelling Pipelines: Design and deploy end-to-end automated labelling systems using frameworks like Snorkel, Cleanlab, or custom active learning loops.
 </li>
 <li>
 Develop "Human-in-the-Loop" (HITL) Systems: Build interfaces and workflows where models pre-label data and humans only intervene on high-uncertainty samples.
 </li>
 <li>
 Quality Assurance &amp; Denoising: Implement algorithmic checks to identify and correct mislabelled or "noisy" data within existing datasets.
 </li>
 <li>
 Tooling &amp; Integration: Collaborate with software engineers to integrate labelling tools with our existing data lakes and ML training infrastructure.
 </li>
 <li>
 Model Optimization: Fine-tune "teacher" models to generate high-quality pseudo-labels for "student" models.
 </li>
 <li>
 Set up and maintain robust data preparation infrastructure&mdash;optimising for data quality, speed, and seamless integration with downstream MLOps pipelines.
 </li>
 <li>
 Perform data visualization and in-depth analysis using advanced data and feature engineering techniques. You&rsquo;ll help transform raw data into actionable insight, supporting both research and deployment.
 </li>
 <li>
 Work closely with Data Scientists, Software Engineers, and Product teams to ensure high data quality and usability across products and projects.
 
 
 
 </li>
 </ul>
 
 About you
 
 
 
 <ul>
 <li>
 At least 8+ years of professional experience in Machine Learning engineering, specifically focused on data centric-AI or computer vision/NLP pipelines.
 </li>
 <li>
 Proficiency in Python: Mastery of the Machine Learning stack (PyTorch or TensorFlow, NumPy, Pandas, Scikit-learn).
 </li>
 <li>
 Automated Labelling Expertise: Proven experience with Weak Supervision (labelling functions) or Active Learning strategies (uncertainty sampling, diversity sampling).
 </li>
 <li>
 Data Engineering: Experience with SQL and NoSQL databases, and managing large-scale unstructured data (images, text, or audio).
 </li>
 <li>
 Cloud Infrastructure: Familiarity with AWS (SageMaker Ground Truth), GCP (Vertex AI), or Azure ML labelling services.
 </li>
 <li>
 Version Control for Data: Experience with DVC (Data Version Control) or similar tools to track dataset iterations.
 </li>
 <li>
 Hands-on expertise building auto-labelling solutions or working with large-scale data annotation workflows.
 </li>
 <li>
 Advanced skills in Python (and/or other relevant languages), and experience with key ML/data science libraries (e.g. TensorFlow, PyTorch, scikit-learn, pandas).
 </li>
 <li>
 Experience designing, deploying, and maintaining scalable data pipelines, including data cleansing, transformation, and storage (cloud, on-prem, or hybrid).
 </li>
 <li>
 Strong background in feature engineering, data analysis, and data visualization&mdash;comfortable using tools like Jupyter, Tableau, or Power BI.
 </li>
 <li>
 Great communicator who documents solutions clearly and collaborates effortlessly across technical and non-technical teams.
 </li>
 <li>
 Able to balance speed and quality, stay curious about new developments, and deliver results in a fast-moving environment.
 </li>
 <li>
 Bachelor&rsquo;s or Master's degree in computer science, Engineering, Mathematics, Data Science, or a related field.
 
 
 
 </li>
 </ul>
 Dyson is an equal opportunity employer. We know that great minds don&rsquo;t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity.
</div>

Lead Data Intelligence Machine Learning Engineer

Naffco

<div>Job Summary
We are seeking an AI Engineer to lead the introduction and adoption of agentic AI technologies across the group. You will design, develop, and implement enterprise AI solutions that improve productivity, automation, decision-making, and operational efficiency across industrial, manufacturing, corporate, and support functions.
You will have hands-on experience with modern AI ecosystems, including OpenAI platforms, the Anthropic Claude ecosystem, and Microsoft Copilot Studio. You will bring expertise in enterprise architecture, data lakes, AI agents, LLM integration, and business transformation.
Key Responsibilities<ul><li>
Design and implement enterprise agentic AI solutions across key functions, including manufacturing, finance, HR, procurement, supply chain, sales, customer service, and industrial operations.</li><li>
Develop AI assistants, copilots, autonomous agents, and workflow automation using:<ul><li>
Microsoft Copilot Studio</li><li>
Azure OpenAI Service</li><li>
Anthropic Claude ecosystem</li><li>
LLM APIs and orchestration frameworks</li></ul></li><li>
Lead enterprise data lake and AI-ready platform architecture, integrating ERP, CRM, manufacturing, IoT, and operational systems.</li><li>
Partner with stakeholders to identify, evaluate, prioritize, and implement AI use cases with measurable ROI.</li><li>
Build secure AI frameworks aligned with cybersecurity, governance, compliance, and enterprise standards.</li><li>
Develop Retrieval-Augmented Generation (RAG) solutions for enterprise knowledge bases and operational data sources.</li><li>
Design AI agents for autonomous decision support, workflow execution, predictive analysis, and recommendations.</li><li>
Establish AI governance standards, responsible AI practices, model monitoring, and prompt engineering standards.</li><li>
Collaborate with infrastructure, cloud, cybersecurity, and application teams to deploy scalable AI environments.</li><li>
Run AI innovation workshops, enable users, and build internal AI capabilities.</li><li>
Support executive leadership in defining enterprise AI strategy and the product roadmap.</li></ul>
Technical Skills &amp; Requirements<ul><li>
Bachelor&rsquo;s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or related field.</li><li>
3+ years of experience in AI/ML engineering, enterprise automation, or digital transformation.</li><li>
Strong hands-on experience with:<ul><li>
Microsoft Copilot Studio</li><li>
Azure OpenAI Service</li><li>
Anthropic Claude ecosystem</li><li>
LLM integration and prompt engineering</li><li>
AI orchestration and autonomous agents</li></ul></li><li>
Experience with Python, REST APIs, LangChain, Semantic Kernel, vector databases, embeddings, and AI workflow automation.</li><li>
Understanding of data lake architecture, ETL pipelines, structured/unstructured processing, and enterprise integrations.</li><li>
Experience integrating AI solutions with ERP systems such as Oracle ERP, HRMS, manufacturing, CRM, and industrial systems.</li><li>
Familiarity with Microsoft Azure, AWS, or Google Cloud.</li><li>
Knowledge of industrial/manufacturing environments, IoT data, predictive maintenance, and operational analytics is highly preferred.</li><li>
Experience with AI governance, cybersecurity, compliance, and enterprise architecture.</li><li>
Strong communication and stakeholder management skills.</li></ul>
Preferred Skills<ul><li>
Experience in manufacturing or industrial sectors.</li><li>
Experience with AI agents, multi-agent frameworks, and autonomous workflow systems.</li><li>
Knowledge of Power Platform, Power Automate, Fabric, Databricks, and enterprise analytics platforms.</li><li>
AI certifications from Microsoft, OpenAI, or other leading AI platforms are an advantage.</li></ul></div>

AI Engineer – Agentic AI & Enterprise Automation

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

DICETEK LLC

<div>We are looking for a skilled and motivated AI Engineer to join our team, with a strong focus on developing applications using Large Language Models (LLMs) and related technologies. The ideal candidate will have experience working with modern LLM frameworks, prompt engineering, vector databases, and structured data integration. You will play a key role in designing, building, and deploying intelligent solutions that interact with unstructured and structured data for advanced query and visualization use cases.<h3 class="jobSectionHeader"> 
Key Responsibilities:</h3><ul><li>
Design and develop AI-driven applications leveraging LLMs (OpenAI, Hugging Face models, or local LLMs)</li><li>
Build and optimize workflows using frameworks like LangChain, LlamaIndex, or Haystack</li><li>
Engineer effective prompts for various use cases, ensuring accuracy and consistency</li><li>
Integrate text-to-SQL models to convert natural language queries into database operations</li><li>
Work with vector databases (FAISS, Chroma, Pinecone) for semantic search and retrieval tasks</li><li>
Implement document processing pipelines including PDF ingestion, text chunking, and embedding generation</li><li>
Generate interactive data visualizations using Plotly, Vega-lite, or JSON-based charting tools</li><li>
Collaborate with data engineers, analysts, and product teams to deliver robust AI solutions</li><li>
Maintain clean, modular, and scalable Python code</li></ul><h3 class="jobSectionHeader">
Required Skills:</h3><ul><li>
Strong experience with LLM frameworks (e.g., LangChain, LlamaIndex, Haystack)</li><li>
Familiarity with LLM APIs such as OpenAI, Cohere, or local models via Hugging Face</li><li>
Hands-on experience with prompt engineering and model fine-tuning (preferred)</li><li>
Proficiency in vector databases: FAISS, Pinecone, or Chroma</li><li>
Solid understanding of document processing: text chunking, embedding strategies, and retrieval pipelines</li><li>
Knowledge of text-to-SQL model integration and query optimization</li><li>
Experience with data visualization tools: Plotly, Vega-lite, or equivalent</li><li>
Strong command of SQL and Python</li><li>
Excellent problem-solving skills and ability to work in a fast-paced environment</li></ul></div>

AI Engineer (LLM & Data Applications)

Explore 664+ Intelligence engineer in Dubai this June. Find roles across top companies and apply now to boost your career.

664 intelligence engineer jobs In Dubai

IT Engineer (Chinese Speaker – AI & CRM Specialist)

AI Engineer – Generative AI and Automation

Lead Data Intelligence Machine Learning Engineer

AI Engineer – Agentic AI & Enterprise Automation

Machine Learning Systems Engineer

AI Engineer (LLM & Data Applications)

AI Engineer (LLM & Data Applications)