Direct message the job poster from X4 Technology
Overview
My Client are developing advanced AI systems that rely on large language models (LLMs), retrieval-augmented generation (RAG), and agentic AI frameworks to deliver accurate, real-time insights. To achieve production-grade reliability, scalability, and seamless integration with existing platforms, we require an ML engineer with strong expertise in AI / ML methods, Python programming, and modern deployment practices. This role must bridge cutting-edge model development with robust service and API engineering, ensuring smooth integration, streaming capabilities, and optimized deployment. Experience with cloud platforms and vector databases, is desirable.
Must Have
- Hands-on experience with large language models (LLMs) and retrieval-augmented generation (RAG) .
- Experience with agentic AI frameworks (e.g., LangChain, LangGraph).
- Strong background in core AI / ML techniques (e.g., supervised / unsupervised learning, deep learning, NLP).
- Proficient programming skills in Python , including experience with common ML / AI libraries (e.g., PyTorch, TensorFlow, scikit-learn).
- Solid understanding of service and API engineering , including real-time / streaming implementation and hardware / software compatibility checks .
- Experience with integration and release engineering : shipping new versions to production, integrating with other system components, and assessing impact on end-to-end performance.
- Hands-on experience in model deployment (e.g., containerization, orchestration with Docker / Kubernetes, inference optimization).
Nice to Have
Experience with cloud platforms (Azure), including AI / ML services.Knowledge of vector databases for retrieval applications.Familiarity with observability and monitoring for deployed ML / AI systems (logging, tracing, metrics).Seniority level
Mid-Senior levelEmployment type
ContractJob function
Information TechnologyIndustries
Technology, Information and Media#J-18808-Ljbffr