Lead AI/ML Engineer

<h1 id="job-description-lead-aiml-engineer">Job Description – Lead AI/ML Engineer</h1><p>14 Oct 2026 · <span class="ldoc-mention">@Shruti</span></p><p><strong>Experience:</strong> 4–6 years · <strong>Type:</strong> Full-time · <strong>Location:</strong> Bengaluru</p><h2 id="about-the-role">About the role</h2><p>We are hiring a hands-on Lead AI/ML Engineer to design, build and ship production AI systems, from agentic LLM applications to classical ML models. You will own solutions end to end, guide a small team, and turn business problems into reliable AI products.</p><h2 id="key-responsibilities">Key responsibilities</h2><ul><li>Design and build agentic AI systems with planning, tool calling, memory and multi-agent workflows using LangChain and LangGraph.</li><li>Architect and optimise RAG pipelines: chunking, embeddings, vector search, re-ranking and evaluation.</li><li>Build, train and deploy traditional ML and deep learning models with scikit-learn, PyTorch and TensorFlow.</li><li>Write production-grade Python, expose models as APIs, and deploy on cloud with MLOps best practices.</li><li>Lead and mentor ML/AI engineers, review code and designs, and partner with product and business teams.</li></ul><h2 id="required-skills">Required skills</h2><ul><li>4–6 years of overall experience, including at least 1–2 years building LLM or GenAI applications.</li><li>Expert-level Python (NumPy, Pandas, FastAPI, async).</li><li>Hands-on experience with Agentic AI, LangChain, LangGraph and RAG.</li><li>Practical experience with vector databases such as Pinecone, Weaviate, Qdrant, Milvus, Chroma or FAISS.</li><li>Strong traditional ML skills with scikit-learn, PyTorch and TensorFlow, plus solid statistics and model evaluation.</li><li>Working knowledge of Git, Docker and a cloud platform (AWS, Azure or GCP).</li><li>Bachelor's or master's degree in computer science, AI, Data Science or a related field.</li></ul><h2 id="nice-to-have">Nice to have</h2><ul><li>LLM fine-tuning (LoRA/QLoRA), LLM evaluation tools (LangSmith, Ragas) and MLOps tools (MLflow, SageMaker).</li></ul>