Machine Learning Engineer – Generative AI (LLMs / RAG / Agentic AI)
Stellar TechnologiesUnited Arab Emirates3 days ago
Full-timeEngineering, Information Technology
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Role Summary
Stellar Technologies is seeking a Machine Learning Engineer (GenAI) to design, build, and deploy next-generation AI systems combining Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI frameworks.
In this role, you will bridge model development and production engineering — developing scalable AI pipelines, integrating real-time APIs, and ensuring high-performance AI services that power enterprise-grade solutions. You will work at the intersection of machine learning, cloud infrastructure, and applied research, collaborating with top engineers and data scientists to deliver intelligent, production-ready AI capabilities.
Key Responsibilities
Job Type: Full Time
Job Location: Abu Dhabi
Stellar Technologies is seeking a Machine Learning Engineer (GenAI) to design, build, and deploy next-generation AI systems combining Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI frameworks.
In this role, you will bridge model development and production engineering — developing scalable AI pipelines, integrating real-time APIs, and ensuring high-performance AI services that power enterprise-grade solutions. You will work at the intersection of machine learning, cloud infrastructure, and applied research, collaborating with top engineers and data scientists to deliver intelligent, production-ready AI capabilities.
Key Responsibilities
- Develop and optimize AI systems leveraging LLMs, RAG, and agentic AI frameworks (LangChain, LangGraph).
- Build and deploy production-grade ML pipelines with real-time inference and retrieval components.
- Design and manage APIs and streaming services to integrate AI models into enterprise platforms.
- Implement containerized, orchestrated deployments using Docker, Kubernetes, and Azure ML.
- Automate data preprocessing, model training, evaluation, and versioning pipelines.
- Collaborate with cross-functional teams to integrate models into front-end, analytics, and automation workflows.
- Ensure governance, compliance, and security of deployed AI workloads.
- Conduct performance benchmarking and optimize inference latency and cost.
- Monitor AI systems in production using observability frameworks (logging, metrics, tracing).
- Participate in architecture discussions to enhance scalability and reliability of AI services.
- Strong hands-on experience with LLMs, RAG, and agentic frameworks (LangChain, LangGraph, Semantic Kernel, etc.).
- Proficiency in Python, with deep understanding of ML libraries like PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers.
- Solid experience in API and microservices engineering (FastAPI, Flask).
- Familiarity with streaming architectures and real-time data handling.
- Knowledge of cloud platforms (Azure preferred), including Azure AI, Cognitive Services, and ML Ops.
- Experience with containerization and orchestration (Docker, Kubernetes).
- Understanding of vector databases (Pinecone, Weaviate, FAISS) and retrieval mechanisms.
- Experience in CI/CD, model deployment, and production monitoring.
- Exposure to GPU-based inference optimization and serverless deployment.
- Knowledge of observability and monitoring tools for AI (Prometheus, Grafana, Azure Monitor).
- Experience in model fine-tuning, prompt engineering, or agentic orchestration.
- Understanding of AI governance, ethical AI, and data privacy frameworks.
- Strong analytical and problem-solving mindset.
- Excellent collaboration and communication skills.
- Passion for innovation, experimentation, and applied AI.
Job Type: Full Time
Job Location: Abu Dhabi
Key Skills
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