AI Engineer

Role Overview

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.

Requirements

• 3–8 years in AI/ML/Applied ML Engineering; minimum 2 production deployments.
• Proficiency in Python, PyTorch or TensorFlow.
• Experience with cloud platforms (Azure/AWS/GCP), Docker/K8s, and CI/CD.
• Practical knowledge of prompting, RAG, vector DBs (FAISS/PGVector/Weaviate/Milvus), and fine-tuning or adapters (LoRA/QLoRA).
• Ability to profile/optimize inference (batching, quantization).
• Bachelor’s/Master’s in CS/EE/Math/AI/related fields.

Skills

• Python
• PyTorch
• TensorFlow
• Docker
• MLflow