Senior AI Engineer, Bangalore
Sourceo7–10 yrsBengaluruOn-siteDirect career pageEst. 30–55 LPA
Posted on 16 Sept
Reach people at Sourceo
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 Sourceo 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 development of generative and optimization AI models for manufacturing process simulation, scheduling, and predictive analytics.
- Manage AI pipelines including synthetic data generation, model training, validation, and deployment for industrial applications.
- Integrate embedded AI and Gen AI with real-time industrial data streams ensuring high availability, low latency, and scalability in manufacturing operations.
Minimum Requirements
- 7-10 years experience with relevant Bachelor’s degree or 4-6 years with Master’s or 1-3 years with PhD in Computer Science, AI, Data Science, Mathematics, or similar quantitative field.
- Strong expertise in generative AI models, Amazon Bedrock, AWS AI/ML services, and building/managing Agentic AI systems using frameworks like LangChain or AutoGen.
- Proficiency in cloud-native architectures, LLMOps, and MLOps tools with knowledge of security, cost, and governance for Gen AI on cloud.
- Must work onsite full-time in Bangalore; Visa sponsorship not available.
Ideal Candidate Profile
- Experienced in industrial AI applications, particularly manufacturing process simulation, predictive maintenance, and digital twin technologies.
- Skilled in advanced AI optimization techniques including multi-objective, non-linear, evolutionary, and constraint-based methods.
- Able to lead and mentor AI teams integrating AI models with real-time manufacturing systems and deploying enterprise-grade AI solutions at scale.