Role & responsibilities

Job description

I) Machine Learning Engineer / Generative AI & Agentic Systems

Masters or Bachelors degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Robotics, Engineering, Mathematics, or a related field.

Professional experience of 2 to 3 years in machine learning engineering, data science, AI engineering, generative AI engineering, or a related technical role.

Proven experience developing and deploying machine learning or deep learning models for real-world applications, especially in Automotive industries

Strong Python programming skills, including experience building maintainable, tested, production-oriented software. Knowledge of other programming languages, notably C++ or .NET, is a significant plus.

Strong knowledge of machine learning architectures, techniques, and evaluation methods, particularly in computer vision, deep learning, anomaly detection, forecasting, optimisation, and generative AI.

Experience with LLM, embedding models, transformer architectures, prompt engineering, fine-tuning, inference optimisation, and model evaluation.

Hands-on experience with Azure OpenAI Service or equivalent LLM platforms for building enterprise-grade generative AI applications.

Experience building RAG systems, including document ingestion, chunking, embedding generation, vector search, semantic search, reranking, grounding, citation generation, and retrieval evaluation.

Experience with Azure AI Search, vector databases, semantic search platforms, or enterprise search systems.

Experience designing or implementing agentic AI systems, including tool calling, API integration, workflow orchestration, planning, multi-agent collaboration, structured outputs, memory, guardrails, and human approval mechanisms.

Experience or strong familiarity with Model Context Protocol, including MCP server development, MCP tool integration, secure data access, and connecting agents to enterprise systems.

Familiarity with agentic AI frameworks such as Azure AI Foundry Agent Service, Microsoft Agent Framework, Semantic Kernel, LangChain, LangGraph, AutoGen, CrewAI, or equivalent orchestration frameworks.

Ability to design AI agents that interact with databases, APIs, documents, business systems, and internal tools using secure and auditable integration patterns.

Ability to analyse complex data, identify practical opportunities, and translate technical findings into actionable business recommendations.

Strong communication skills, with the ability to explain technical concepts clearly to technical and non-technical stakeholders.

Ability to work effectively in cross-functional and Agile environments.

Self-motivated, pragmatic, and comfortable operating in fast-moving technical environments. Role & responsibilities