Lead AI/ML Software Use Cases Validation Engineer

amd

Bangalore 8 Years Exp Posted 8d ago

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
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

8–12 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)