AI Software Engineer - AI Frameworks
Intel Corporation (company site, opens in a new tab)6–12 yrsBengaluruOn-siteDirect career pageEst. 35–65 LPA
Posted 13h ago
Reach people at Intel Corporation
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 Intel Corporation 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
- Design and develop GPU kernels for AI framework operations (attention mechanisms, collective operations, computation primitives) optimized for Intel accelerators and GPUs.
- Optimize AI framework components including scheduling, memory management, and execution pipelines to improve throughput, latency, and resource use.
- Collaborate with open-source communities (SGLang, vLLM, PyTorch) to integrate innovations and optimize frameworks for production AI workloads.
Minimum Requirements
- Bachelor's (B.Tech) or Master's (M.S./M.Tech) degree in Computer Science, Electronics and Communications Engineering, or related field.
- 6 to 12 years of professional experience in AI framework development and GPU kernel optimization.
- Advanced C++ (C++14/17) proficiency and intermediate Python and parallel programming skills.
- On-site work required in Bangalore, India.
Ideal Candidate Profile
- Expertise in kernel development and optimization for machine learning operations such as GEMM, Flash Attention, and sampling in production-grade AI frameworks.
- Deep knowledge of AI framework internals including scheduling, memory management, distributed execution, and hardware-software co-optimization.
- Experience contributing to or collaborating with open-source AI framework projects and optimizing multi-GPU and distributed AI workloads.