Lead AI/ML Software Use Cases Validation Engineer
AMD · Bangalore · 12+ yrs experience · Posted 2026-05-07
Tech stack: Linux, Python
About the role
AI/ML Software Use Cases Validation Engineer (Lead) About the Role Join AMD’s PAVS team as a Robotics Usecases Validation Engineer where you will Validate and Execute diverse Robotics platforms, variants and customer usecases for advanced robotics systems across software, hardware, and integrated platforms. Your work will ensure safety, reliability, and performance through rigorous testing in simulation, SIL/HIL environments, and real-world deployments.
Responsibilities:
- Join AMD’s PAVS team as a Robotics Usecases Validation Engineer where you will Validate and
- Execute diverse Robotics platforms, variants and customer usecases for advanced robotics systems across software, hardware, and integrated platforms. Your work will ensure safety, reliability, and performance through rigorous testing in simulation, SIL/HIL environments, and real-world deployments.
- Lead validation and quality ownership of AI/ML compute stacks on Ubuntu and Yocto
- Define validation strategy, test architecture, and coverage across functional, performance, stress, regression, and scalability testing
- Own and drive the defect lifecycle, including triage, root cause analysis, and closure
- Validate end‑to‑end AI pipelines, including: Model training, conversion, and optimization (e.g., PyTorch → ONNX) Kernel execution, memory transfers, and inference accuracy
- Model training, conversion, and optimization (e.g., PyTorch → ONNX)
- Kernel execution, memory transfers, and inference accuracy
- Define and execute AI benchmarking and profiling strategies for training and inference workloads
- Analyze compute, memory, and latency bottlenecks and drive system‑level and model‑level optimizations
- Validate AI frameworks and runtimes ( PyTorch, TensorFlow, ONNX Runtime )
- Execute and optimize workloads on ROCm/HIP, CUDA, OpenCL, and heterogeneous accelerators
- Design and own Python‑based automation frameworks for validation, benchmarking, and reporting
- Drive improvements in validation scalability, efficiency, and performance coverage
- Collaborate closely with compiler, runtime, driver, and hardware teams
- Provide technical leadership and mentorship to senior and junior engineers
- Communicate validation status, performance metrics, and quality risks to stakeholders
- Required
Qualifications:
- 12 years of experience in AI/ML software validation or performance engineering
- Strong expertise in Python scripting and test automation
- Strong ML fundamentals including deep learning and LLMs
- Hands‑on experience with ROCm validation, performance profiling, and optimization
- Experience with HIP, CUDA, OpenCL, and TensorFlow/PyTorch integrations
- Proven experience validating end‑to‑end AI pipelines
- Strong Linux expertise ( Ubuntu, Yocto )
- Validation & Process
- Performance‑driven validation mindset with focus on production readiness
- Ability to lead initiatives independently with strong ownership
- Soft Skills
- Strong analytical and problem‑solving skills with clear written and verbal communication, and the ability to collaborate effectively with global, cross‑functional teams.
Qualifications
- 12 years of experience in AI/ML software validation or performance engineering
- Strong expertise in Python scripting and test automation
- Strong ML fundamentals including deep learning and LLMs
- Hands‑on experience with ROCm validation, performance profiling, and optimization
- Experience with HIP, CUDA, OpenCL, and TensorFlow/PyTorch integrations
- Proven experience validating end‑to‑end AI pipelines
- Strong Linux expertise ( Ubuntu, Yocto )
- Validation & Process
- Performance‑driven validation mindset with focus on production readiness
- Ability to lead initiatives independently with strong ownership
- Strong analytical and problem‑solving skills with clear written and verbal communication, and the ability to collaborate effectively with global, cross‑functional teams.
Responsibilities
- Join AMD’s PAVS team as a Robotics Usecases Validation Engineer where you will Validate and Execute diverse Robotics platforms, variants and customer usecases for advanced robotics systems across software, hardware, and integrated platforms.
- Your work will ensure safety, reliability, and performance through rigorous testing in simulation, SIL/HIL environments, and real-world deployments.
- Lead validation and quality ownership of AI/ML compute stacks on Ubuntu and Yocto
- Define validation strategy, test architecture, and coverage across functional, performance, stress, regression, and scalability testing
- Own and drive the defect lifecycle, including triage, root cause analysis, and closure
- Validate end‑to‑end AI pipelines, including: Model training, conversion, and optimization (e.g., PyTorch → ONNX) Kernel execution, memory transfers, and inference accuracy
- Model training, conversion, and optimization (e.g., PyTorch → ONNX)
- Kernel execution, memory transfers, and inference accuracy
- Define and execute AI benchmarking and profiling strategies for training and inference workloads
- Analyze compute, memory, and latency bottlenecks and drive system‑level and model‑level optimizations
- Validate AI frameworks and runtimes ( PyTorch, TensorFlow, ONNX Runtime )
- Execute and optimize workloads on ROCm/HIP, CUDA, OpenCL, and heterogeneous accelerators
- Design and own Python‑based automation frameworks for validation, benchmarking, and reporting
- Drive improvements in validation scalability, efficiency, and performance coverage
- Collaborate closely with compiler, runtime, driver, and hardware teams
- Provide technical leadership and mentorship to senior and junior engineers
- Communicate validation status, performance metrics, and quality risks to stakeholders