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Job Description
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 strong 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.