Description

You validate the AI software stack end-to-end by developing and executing representative ML workloads as a proxy for real-world users.

This role is on-site.

Responsibilities

• Write, port, and optimize AI/ML workloads to identify performance bottlenecks, functional gaps, and usability issues.
• Develop and maintain a comprehensive validation test suite covering model serving, kernel compilation, runtime, and framework integration layers.
• Reproduce, triage, and analyze issues across the stack, from Python-level framework behavior to low-level compiled kernel correctness and GPU performance.
• Benchmark and profile workloads to monitor regressions and validate optimization improvements across releases.
• Design and implement scalable test frameworks and automation infrastructure to enable continuous integration and validation.

Required Skills

• 5+ years of experience in AI/ML systems, GPU programming, or software validation.
• Strong hands-on experience with CUDA and GPU architectures.
• Proficiency with ML frameworks such as PyTorch.
• Experience profiling and optimizing ML workloads for performance and latency.
• Solid understanding of AI software stacks including compilers, runtimes, and framework integration.
• Strong debugging skills across multi-layered software systems.
• Experience with software validation and end-to-end testing.

Preferred Skills

• Exposure to hardware accelerators and performance benchmarking tools.
• Knowledge of kernel debugging techniques.

Key Skills

Education

Any Graduate