Senior Machine Learning Engineer

Experience: Minimum 7+ years

Budget: ₹25 – ₹40 LPA

Joining: Only Immediate Joiners

We are looking for a Senior Machine Learning / GenAI Engineer who can design, build, and deploy production-grade AI/ML systems end-to-end. The ideal candidate will have strong experience in Machine Learning, Generative AI, and scalable ML infrastructure, with the ability to develop intelligent applications using modern AI frameworks and cloud platforms.

This role requires hands-on expertise in ML model development, GenAI architectures, RAG pipelines, and deployment of ML services in production environments.

Key Responsibilities

- Design, build, and deploy production-grade AI/ML solutions end-to-end. - Develop scalable Machine Learning and Generative AI applications using Python and SQL. - Build, train, and fine-tune ML models using libraries such as Scikit-learn, XGBoost, and LightGBM. - Work on NLP and Generative AI initiatives leveraging frameworks such as Hugging Face, LangChain, and LlamaIndex. - Implement and integrate vector database–based solutions for semantic search, retrieval systems, and RAG pipelines. - Develop and deploy ML/GenAI APIs and services using FastAPI or Flask. - Containerize and deploy applications using Docker and Kubernetes. - Work with cloud-native ML platforms such as AWS SageMaker, GCP Vertex AI, or Azure ML. - Integrate and utilize Text-to-SQL models such as SQLCoder for intelligent data querying and automation.

Required Skills

- Strong programming expertise in Python and SQL. - Solid understanding of machine learning algorithms and the ML lifecycle. - Hands-on experience with Generative AI, LLMs, embeddings, vector databases, and RAG architectures. - Experience building and deploying ML APIs and production ML services. - Experience with cloud platforms (AWS / GCP / Azure) for ML deployment. - Experience with containerization and orchestration (Docker, Kubernetes). - Familiarity with NLP frameworks and LLM ecosystems such as Hugging Face, LangChain, or LlamaIndex.