Debug and optimize complex multi-layered systems involving kernel execution, memory hierarchies, and distributed AI scenarios.
Qualifications
Qualifications
Bachelor's degree (B.Tech) or Master's degree (M.S./M.Tech) in Computer Science, Electronics and Communications Engineering (ECE), or a related field, with 6 to 12 years of professional experience.
Advanced proficiency in C++ (C++14/17) and intermediate skills in Python and parallel programming.
Proven, hands-on experience writing and optimizing GPU kernels. Demonstrated expertise in kernel development for machine learning operations such as GEMM, attention mechanisms (including Flash Attention), collective operations, and sampling.
In-depth, hands-on experience with AI frameworks—SGLang, vLLM, PyTorch, or similar production-grade serving and training systems. Deep understanding of their internal architecture, scheduling mechanisms, and memory management strategies is essential.
Strong knowledge of AI inference and training concepts including batching strategies, memory optimization, distributed execution, and performance tuning.
Practical experience optimizing and deploying AI models at scale in production environments.
Strong ability to debug complex issues in multi-layered software systems, performance profiling, and bottleneck identification in AI frameworks.
Solid understanding of computer architecture, GPU execution models, memory hierarchies, and hardware-software co-optimization techniques.
Experience working on frameworks and platforms that have been deployed to production with high availability and performance requirements.
Excellent communication skills and experience collaborating with cross-functional, geographically distributed teams.
Preferred Qualifications
Extensive experience developing production-grade kernels with CUDA, CUTLASS, or Triton for various AI operations.
Published or open-source contributions demonstrating kernel optimization expertise.
Knowledge of compiler algorithms for heterogeneous systems and kernel fusion optimizations.
Contributions to or deep familiarity with SGLang, vLLM, PyTorch, or other open-source AI frameworks.
Experience with distributed AI workloads, multi-GPU scheduling, and optimization across heterogeneous hardware.
Understanding of quantization techniques, mixed-precision inference and training, and their integration into AI frameworks.
Job Type
Experienced Hire
Shift
Shift 1 (India)
Primary Location
India, Bangalore
Additional Locations
Posting Statement
All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.
- Work Model for this Role
- This role will require an on-site presence. * Job posting details (such as work model, location or time type) are subject to change.
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