AI/ML Engineer

AI/ML Engineer with 5–7 years of experience in developing building AI/GenAI solutions, and contributing to scalable AI platforms. The ideal candidate should have strong hands‑on engineering skills and experience delivering ML features into production.

Key Responsibilities

Build components of Generative AI solutions, including prompt engineering, embeddings, vector search, and RAG workflows.

Develop clean, production‑ready code and contribute to MLOps pipelines, including CI/CD for ML, model monitoring, and versioning.

Work closely with product and architecture teams to understand requirements and translate them into technical implementations.

Perform data analysis, feature engineering, and experiment tracking.

Collaborate with senior engineers to improve system design, performance, and model quality.

Required Skills

Proficiency in Python and ML libraries (PyTorch, TensorFlow, Scikit‑learn).

Working knowledge of LLMs, embeddings, vector databases (FAISS/Milvus/Pinecone).

Experience with data pipelines, model deployment, and cloud platforms (Azure, AWS, or GCP).

Strong grounding in ML fundamentals: algorithms, metrics, tuning, and evaluation.

Good understanding of software engineering principles, Git workflows, and APIs.

Exposure to RAG systems, LangChain, or LlamaIndex.

Nice-to-Have

Experience with Docker/Kubernetes or cloud-native deployments.

Knowledge of Responsible AI, model governance, or domain‑specific compliance.