Key Responsibilities
- Model Development: Train, fine-tune, and optimize generative models (LLMs, Diffusion Models) using techniques like LoRA, QLoRA, and PPO.
- RAG & Agentic Workflows: Architect scalable, multi-agent systems and retrieval mechanisms using orchestration frameworks like LangChain, LangGraph, or AutoGen.
Required Technical Skills
- Programming Languages: Advanced proficiency in Python (mandatory)
- AI Tooling & Frameworks: Hands-on experience with PyTorch.
- Vector Databases: Proficient in managing vector storage for high-performance retrieval (e.g., Pinecone, Milvus, Qdrant, Chroma).
- Cloud & Infrastructure: Experience containerizing applications (Docker, Kubernetes) and deploying on AWS, GCP
- Deep learning model fine-tuning (Hyper parameter)
- Phd in Machine learning/Deep Learning with 2 years experience in proven research in AI and paper publications in conferences.
- Good to have :Open source contributions
Pay: ₹700,000.00 - ₹900,000.00 per year
Benefits:
- Flexible schedule
- Health insurance
- Paid sick time
- Provident Fund
Education:
Experience:
- Deep learning: 3 years (Required)
Work Location: In person
