Lead Data Scientist
Innova Software Services5+ yrsBengaluruOn-siteDirect career pageEst. 20–35 LPA
Posted on 24 Sept
Reach people at Innova Software Services
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Innova Software Services you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead design and delivery of production-ready Generative AI solutions using large language models, advanced RAG pipelines, and agentic workflows.
- Develop autonomous multi-agent systems and build semantic search systems leveraging vector databases and LangChain/LlamaIndex frameworks.
- Deploy, manage, and scale machine learning and AI workloads on enterprise cloud platforms, and build robust backend microservices using Python FastAPI.
Minimum Requirements
- 5+ years of relevant hands-on experience in Machine Learning and Data Science.
- Educational Qualification: BE, B.Tech, MCA, or M.Sc degree holders only.
- Proficiency with LLMs, Generative AI (ChatGPT, LLaMA 2, GANs, VAEs), NLP, transformer models, LangChain, Agentic AI concepts, Python FastAPI, and cloud deployment on AWS/Azure/GCP.
- Notice Period: Immediate joiners preferred or candidates actively serving notice period.
Ideal Candidate Profile
- Experienced in architecting end-to-end AI systems with hands-on use of advanced models and retrieval-augmented generation.
- Skilled in building scalable AI backend infrastructures and deploying models in production in cloud environments.
- Capable of leading complex AI projects that incorporate multi-agent and agentic AI workflows in a Bangalore-based, onsite setting.