AI Software Stack Engineer

As an AI Software Stack Engineer at a Global Semiconductor Company in Bangalore, India, your role involves working on a next-generation software stack for high-performance execution on custom hardware. Your primary mission is to develop an optimized, modular, and deeply integrated platform that ensures industry-leading low-latency systems.

Key Responsibilities:

• Validate the AI software stack end-to-end by developing and running representative ML workloads, acting as a proxy for real users.
• Write from scratch, port, and optimize AI workloads, identifying gaps, performance bottlenecks, and usability issues.
• Develop and maintain a comprehensive suite of validation tests spanning model serving, kernel compilation, and framework integration layers.
• Reproduce, triage, and characterize issues across the stack from Python-level framework behavior down to compiled kernel correctness and performance.
• Benchmark and profile workloads to track performance regressions and validate optimization improvements across stack releases.
• Collaborate closely with compiler, runtime, and framework teams to provide actionable feedback and drive resolution of identified issues.
• Design and implement testing frameworks, platforms, and automation infrastructure to enable continuous and scalable validation across the stack.

Qualifications:

• BSc or higher in Computer Science, Electrical Engineering, or a related field.
• Hands-on experience with ML frameworks such as PyTorch, including model authoring and debugging.
• Familiarity with model serving platforms.
• Experience writing or modifying GPU kernels using Triton, CUDA, or similar kernel authoring tools.
• Strong Python skills and comfort working across multiple layers of a complex software stack.
• Systematic debugging mindset with the ability to isolate issues across framework, compiler, and runtime boundaries.

Strong Advantage:

• Experience enabling new model architectures or workloads on AI accelerator platforms.
• Hands-on experience with performance profiling and benchmarking tools for ML workloads.
• Understanding of compiler-generated code behavior and ability to read and reason about IR-level representations.
• Experience with CI/CD pipelines and automated test infrastructure for ML systems.
• Exposure to GPU or custom accelerators ecosystems.
• Familiarity with container-based deployment and orchestration for ML serving. As an AI Software Stack Engineer at a Global Semiconductor Company in Bangalore, India, your role involves working on a next-generation software stack for high-performance execution on custom hardware. Your primary mission is to develop an optimized, modular, and deeply integrated platform that ensures industry-leading low-latency systems.

Key Responsibilities:

• Validate the AI software stack end-to-end by developing and running representative ML workloads, acting as a proxy for real users.
• Write from scratch, port, and optimize AI workloads, identifying gaps, performance bottlenecks, and usability issues.
• Develop and maintain a comprehensive suite of validation tests spanning model serving, kernel compilation, and framework integration layers.
• Reproduce, triage, and characterize issues across the stack from Python-level framework behavior down to compiled kernel correctness and performance.
• Benchmark and profile workloads to track performance regressions and validate optimization improvements across stack releases.
• Collaborate closely with compiler, runtime, and framework teams to provide actionable feedback and drive resolution of identified issues.
• Design and implement testing frameworks, platforms, and automation infrastructure to enable continuous and scalable validation across the stack.

Qualifications:

• BSc or higher in Computer Science, Electrical Engineering, or a related field.
• Hands-on experience with ML frameworks such as PyTorch, including model authoring and debugging.
• Familiarity with model serving platforms.
• Experience writing or modifying GPU kernels using Triton, CUDA, or similar kernel authoring tools.
• Strong Python skills and comfort working across multiple layers of a complex software stack.
• Systematic debugging mindset with the ability to isolate issues across framework, compiler, and runtime boundaries.

Strong Advantage:

• Experience enabling new model architectures or workloads on AI accelerator platforms.
• Hands-on experience with performance profiling and benchmarking tools for ML workloads.
• Understanding of compiler-generated code behavior and ability to read and reason about IR-level representations.
• Experience with CI/CD pipelines and automated test infrastructure for ML systems.
• Exposure to GPU or custom accelerators ecosystems.
• Familiarity with container-based deployment and orchestration for ML serving.