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.

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





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

Industry Preferred

Qualifications

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

General Requirements

- 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.

Soft Skills

- Product mindset and problem‑solving.

- Cross‑functional collaboration and crisp communication.

Our commitment to Diversity, Equity, and Inclusion

📌 AI Engineer (Mumbai)
🏢 Mahindra u0026 Mahindra
📍 Mumbai