AI Engineer Responsibilities &

- Key Deliverables We seek AI Engineers who can build and ship production‑grade AI systems (LLMs, NLP, Computer Vision, predictive analytics) across M&M;’s businesses. Candidates must demonstrate robust engineering fundamentals, hands‑on model lifecycle ownership, and enterprise deployment experience. Below are the roles &

responsibilities: Design, train, fine‑tune, and evaluate models; drive A/B experiments and benchmarking. Build scalable data and model pipelines (feature extraction, training, inference, monitoring). Deploy on cloud (Azure/AWS/GCP) using Docker/Kubernetes; implement CI/CD and observability.

Integrate models into services/APIs; ensure SLAs on latency, throughput, and cost. Implement MLOps best practices (MLflow/model registry/versioning, retraining triggers, drift detection).



Collaborate with product/business teams; translate requirements into robust AI solutions.

Experience Experience: 3–8 years in AI/ML/Applied ML Engineering; minimum 2 production deployments.

Tech: Python, PyTorch or TensorFlow; cloud (Azure/AWS/GCP)

- Docker/K8s
- CI/CD
- MLflow or equivalent.

GenAI/LLMs: Practical knowledge of prompting, RAG, vector DBs (FAISS/PGVector/Weaviate/Milvus), and fine‑tuning or adapters (LoRA/QLoRA).

Systems: Ability to profile/optimize inference (batching, quantization).

Work Mode: WFO only; willingness to relocate to Mumbai preferred.

Qualifications Bachelor’s/Master’s in CS/EE/Math/AI/related fields (or demonstrably equivalent experience).

📌 Artificial Intelligence Engineer (Mumbai)
🏢 Mahindra and Mahindra
📍 Mumbai