Python Automation Engineer

Key Responsibilities:

AI/ML Validation & Quality Ownership on Ubuntu & Yocto OS Variants

Lead the Team & Exeuctie validation efforts for complex AI/ML compute stacks across multiple platforms and environments

Define, develop, and execute comprehensive validation plans, test strategies, and methodologies for AI software and system pipelines

Own the defect lifecycle, including reporting, triage, root cause analysis, and closure

Ensure validation coverage across functional, performance, stress, regression, and scalability testing

End to End AI Pipeline Validation

Validate end to end AI workflows, including:

Validate end to end ROCmLibraries

o Model training, conversion, and optimization (e.g., PyTorch ONNX)

o Inference runtimes (ONNX Runtime, TensorRT, ROCm/HIP, OpenVINO)

o Compilers and toolchains (TVM, Vitis AI, XDNA, XLA)

o Kernel execution, memory transfers, and inference accuracy

Validate correctness, stability, and performance of AI workloads on Linux based environments (Ubuntu, Yocto)

AI Benchmarking, Profiling & Optimization

Define and execute AI benchmarking strategies for training and inference workloads across hardware platforms

Perform performance profiling and analysis of AI models to identify compute, memory, and latency bottlenecks

Collaborate with compiler, runtime, and hardware teams to drive model level and system level optimizations

Validate performance improvements across model architectures, batch sizes, precision modes (FP32, FP16, INT8), and execution paths

Ensure performance regressions are detected early and performance KPIs are met for production releases

ML Frameworks & Compute Stack Expertise

Validate integration, functionality, and performance of AI frameworks including PyTorch, TensorFlow, and ONNX Runtime

Execute and validate AI/ML workloads on compute stacks such as ROCm/HIP, CUDA, OpenCL, and heterogeneous accelerators

Analyze performance impact of framework, compiler, and runtime changes on real world AI models

Automation & Tooling

Design and implement Python based validation and benchmarking frameworks

Develop reusable automation for test execution, benchmarking, profiling, result analysis, and reporting

Drive continuous improvements in validation efficiency, benchmarking scalability, and coverage

Technical Leadership & Collaboration

Work closely with architecture, compiler, runtime, driver, and hardware teams to debug performance and functional issues

Provide technical guidance and mentorship to junior engineers and validation teams

Collaborate effectively with global, cross functional teams across time zones

Communicate validation, benchmarking results, performance risks, and quality metrics clearly to stakeholders

Required Skills & Qualifications:

8 to 12 years Experience in AI Validation & Strong Python & Scripting knowledge

Technical Expertise

Strong background in machine learning fundamentals, including:

o Deep learning

o Large Language Models (LLMs)

o Recommender systems

Strong experience with ROCm concepts and ROCm validation

Hands on experience with AI benchmarking, profiling, and performance optimization of AI models

Prior experience validating AI/ML compute stacks, including:

o HIP, CUDA, OpenCL

o OpenVINO

o TensorFlow / PyTorch integrations

Experience validating end to end AI pipelines, including model conversion, inference runtimes, compilers, kernel execution, and accuracy

Strong Python programming skills for automation, benchmarking, and validation

Experience profiling AI workloads to optimize throughput, latency, and resource utilization

Strong knowledge of Linux environments, specifically Ubuntu and Yocto

Validation, Quality & Process

Strong experience with software validation processes, defect management, and SDLC

Experience with production level quality assurance practices and performance driven validation

Strong focus on test quality, performance coverage, reproducibility, and release readiness

Ability to work independently with strong ownership of deliverables

Soft Skills

Excellent problem solving abilities with a performance driven and analytical mindset

Strong verbal and written communication skills

Proven ability to work effectively with global and cross functional teams