Senior AI/ML Engineer
Pune | Full-Time | Onsite
Experience: 6–10 Years
About the Role
We are looking for a Senior AI/ML Engineer to lead enterprise-grade AI system development focused on production RAG systems, deep learning pipelines, semantic retrieval systems, AI orchestration platforms, and scalable AI deployments.
This role requires strong practical implementation depth, architecture ownership capability, and hands-on experience deploying AI systems into production environments.
The selected candidate will directly contribute to scalable AI architecture, advanced retrieval workflows, production ML deployment strategy, and mentoring junior AI engineers.
Key Responsibilities
- Architect enterprise-grade RAG systems
- Build chunking, reranking, retrieval, and hallucination mitigation pipelines
- Design and optimize XGBoost models
- Develop deep learning and LSTM workflows
- Deploy AI models using PyTorch and/or TensorFlow
- Design advanced LangChain / LangGraph orchestration systems
- Build multi-agent AI workflows
- Architect scalable vector database systems
- Lead production AI deployments and optimization
- Mentor junior AI engineers and guide technical implementation
Required Skills
- Enterprise AI implementation experience
- Production RAG system development
- Deep learning implementation
- Strong experience with XGBoost
- PyTorch and/or TensorFlow
- Semantic retrieval systems
- Vector databases
- Advanced LangChain workflows
- LangGraph orchestration
- Production AI deployment exposure
- Strong debugging and optimization capability
Good to Have
- MLflow
- Weights & Biases
- Kubeflow
- Transformer architecture understanding
- Cloud AI services exposure
- Multi-agent AI systems
Who Should Apply
- Engineers who have deployed AI systems into production
- Candidates with enterprise AI implementation exposure
- Developers experienced in scalable retrieval systems
- Engineers comfortable owning AI architecture decisions
- Candidates with strong debugging and optimization maturity
Who Should NOT Apply
- Prompt-engineering-only profiles
- Notebook-only ML practitioners
- Tutorial/demo-level GenAI profiles
- Research-only candidates without deployment exposure
- Candidates without production ownership experience
Eligibility
- 6–10 years of experience
- B.E / B.Tech mandatory
- Strong Machine Learning and AI experience required
- Candidates should be comfortable working onsite from Pune
What We’re Looking For
- Strong practical implementation capability
- Enterprise AI architecture mindset
- Production deployment maturity
- Retrieval optimization expertise
- Leadership and mentoring capability
- Ownership-driven engineering attitude
Job Type
Full-Time
Location
Pune (Onsite)
Hiring Timeline
Immediate hiring preferred
Pay: From ₹1,400,000.00 per year
Benefits:
- Health insurance
- Paid time off
Application Question(s):
- Describe a production AI/ML system you have architected or deployed. Include technologies used, scale, retrieval architecture, deployment environment, and your exact ownership responsibilities.
- Which of the following have you implemented in real production environments?
(RAG Systems, LangChain, LangGraph, Vector Databases, Semantic Search, PyTorch, TensorFlow, XGBoost, Multi-Agent AI Workflows, Production AI Deployment)
- Explain how you handled chunking, reranking, retrieval optimization, or hallucination mitigation in a production RAG or LLM system.
- Have you led AI architecture decisions, mentored engineers, or owned production AI deployment workflows?
- Share GitHub, portfolio, architecture diagrams, case studies, published work, or production AI systems you have contributed to.
Education:
Location:
- Pune, Maharashtra (Pune) (Required)
Work Location: In person
