AI Engineer + Data Scientist

JD

AI Engineer / Developer

Snapshot

Experience: 5–7 years in ML/AI engineering

Reports To: AI Technical Lead / Manager, AIML

Education: B.E./B.Tech or M.Tech in CS, Data Science, or related field

About The Role

Build and ship production-grade GenAI and agentic AI applications that automate enterprise workflows — from design through deployment. A hands-on individual-contributor role for a strong builder.

Key Responsibilities

- Build agentic applications using LangGraph, AutoGen, CrewAI, or Semantic Kernel.
- Design RAG pipelines — chunking, hybrid search, re-ranking, memory, and tool orchestration.
- Deploy and monitor AI workloads on Azure (AKS/ARO) with CI/CD and observability.
- Implement responsible-AI guardrails — prompt-injection defense and content filtering.
- Define evaluation metrics for task success, hallucination, latency, and cost.

Must-Have Skills
- 5+ years ML/AI engineering with production LLM/agentic delivery.
- Advanced Python and at least one agent framework (LangGraph, AutoGen, CrewAI, PydanticAI).
- Solid LLM and prompt-engineering skills (GPT, Claude, LLaMA); hands-on RAG workflows.
- Azure AI stack (Azure OpenAI, AI Search, AI Services) and Databricks ML (MLflow, Delta Lake).
- Vector databases (FAISS, Pinecone, Chroma) and embedding/retrieval design.
- Containerized deployment (Docker/Kubernetes, AKS/ARO) and REST APIs / WebSockets / event-driven services.
- CI/CD and version control (Jenkins / GitHub Actions, Git) with SDLC and agile practices.




- Portfolio of 3+ production AI deployments with measurable business impact.

Nice to Have
- Model fine-tuning (LoRA/PEFT), multi-modal AI, and model evaluation frameworks.
- LLMOps / MLOps and model monitoring (drift, latency, cost, hallucination).
- Knowledge graphs (Neo4j); AWS Bedrock / GCP Vertex AI exposure.
- AI-augmented dev tools (GitHub Copilot, Claude Code, Windsurf) for rapid prototyping.
- Enterprise AI security, compliance, and governance awareness.
- Manufacturing or supply-chain domain experience.

 AI Engineer + Data Scientist - Lead

JD

AI Technical Lead

Snapshot

Experience: 8+ years in ML/AI (incl. DL/RL in production)

Reports To: Manager, AIML

Education: Master's (preferred) or Bachelor's in CS, Data Science, or Mathematics

About The Role

Own the full lifecycle of enterprise-scale AI solutions — architecture through production — and set technical best practices, governance, and standards across the team. A player-coach leadership role.

Key Responsibilities

- Architect end-to-end DL/RL and agentic AI solutions from design to production.
- Set technical standards, governance, and evaluation frameworks across the team.
- Optimize models for production inference (TensorRT/ONNX/Triton); balance accuracy vs.



latency.
- Scale training/inference on Azure ML, AKS/ARO, and distributed infrastructure.
- Lead technical solutioning, manage stakeholders, and mentor engineers.

Must-Have Skills
- 7+ years ML/AI with production DL and/or RL systems.
- Mastery of DL frameworks (PyTorch/TensorFlow/JAX) and strong applied math (linear algebra, probability, optimization).
- Deep learning across CNNs, transformers, and sequence models; RL agents (PPO, SAC, TD3, CQL).
- Inference optimization (TensorRT/ONNX/Triton) and accuracy vs. latency benchmarking.
- Model serving and containerized deployment at scale (Docker/Kubernetes, AKS/ARO).
- Cloud-scale training/inference on Azure ML with distributed training and MLOps/CI-CD.
- Ability to define standards, governance, and evaluation frameworks across a team.
- Proven technical leadership, mentoring, and stakeholder communication.
- Track record of 6–10 production deployments with measurable business impact.

Nice to Have
- Agentic AI architecture (LangGraph, AutoGen, CrewAI) and RAG pipeline design.
- RL libraries (Ray RLlib, Stable-Baselines3, Gymnasium); multi-agent RL and simulation (MuJoCo).
- Model compression/quantization and GPU-efficiency optimization.
- Agentic platform evaluation (Azure AI Foundry, AWS Bedrock, Databricks AgentBricks).
- Optimization/OR background (LP/MIP, Gurobi/CPLEX); Julia/SciML exposure.
- Semiconductor, manufacturing, or supply-chain domain experience.

Skills: cd,azure,ml,optimization

📌 AI Engineer / Developer (Mumbai)
🏢 Zorba AI
📍 Mumbai