Hinduja Tech - Machine Learning Engineer

Job Title : Machine Learning Engineer

About the Role :

Key Responsibilities :

- Work with IT teams to deploy and maintain services in a self-hosted environment.

Job requirements :

You will be responsible for setting up and maintaining the RAG backend infrastructure, ensuring data security and compliance, and integrating multiple data sources into a unified knowledge system. Over time, you will transition into broader engineering tasks, supporting the work of the engineering functions.

Key Responsibilities :

- Design, implement, and maintain scalable data ingestion pipelines for unstructured and structured content.

- Build and manage vector database infrastructure (e.g. Pinecone, Milvus) for document indexing and retrieval.

- Develop and enforce fine-grained access control mechanisms to ensure secure and compliant knowledge access.

- Collaborate with domain experts to source, curate, and structure knowledge for RAG workflows.

- Integrate document chunking, embedding generation, and metadata tagging into the pipeline.

- Monitor and optimise retrieval performance, latency, and quality across the RAG stack.

- Implement observability, logging, and evaluation metrics for pipeline health and retrieval quality.

- Bachelor's or Master's degree in computer science, Data Engineering, or a related field.

- 5 + years of experience in ML Engineering, Data Engineering, or MLOps.

- Proficiency in Python and experience with data manipulation, analysis and visualisation libraries (e.g. Pandas, NumPy, Matplotlib, Seaborn etc.)

- Familiarity with access control models (e.g. RBAC, ABAC) and data governance practices.

- Strong understanding and adherence to the Clean Code principles.

- Experience with Retrieval-Augmented Generation (RAG) architectures.

- Hands on experience with AI-Aided software development (e.g. GitHub Copilot, Cursor, Claude Code)

- Familiarity with LangChain, LlamaIndex, or similar frameworks.

- Exposure to knowledge management systems or enterprise search platforms.

- Experience with containerisation (Docker, Kubernetes).

- Experience with ML/AI frameworks (e.g. SciKit-learn, Keras, PyTorch, TensorFlow).

- Continuous learning mindset and a passion for staying up to date with the latest trends and advancements in data science and machine learning.

- Strong analytical and problem-solving skills.

- Ability to work within a team with a proactive attitude.

- Fluent English.

- Opportunity to work on cutting-edge AI applications in a real-world enterprise setting.

- Professional development opportunities and the possibility to grow the role.