
Validation Automation Engineer
1 week ago
Role : Validation Automation Engineer
We're looking for a skilled Validation Automation Engineer with 3-6 years of experience to join our team in [Insert Location]. The ideal candidate will have a strong background in machine learning validation and be proficient in Python with expertise in Linux/Yocto.
- Strong knowledge on ubuntu / yocto linux Experience working with opensource frameworks such as PyTorch, TensorFlow, and ONNX-Runtime.
- Experience in profiling ML workloads Prior experience in executing validation plans for AI/ML compute stacks such as HIP, CUDA, OpenCL, OpenVINO, ONNX Runtime and TensorFlow/PyTorch integrations.
- Prior experience in validating end-to-end AI pipelines, for e.g. model conversion (e.g., PyTorch - ONNX), Inference runtimes (e.g, ONNX Runtime, TensorRT, ROCm/HIP), compilers/toolchains (e.g. TVM, Vitis AI, XDNA, XLA), kernel execution, memory transfer and inference results
- Strong background in python programming.
- Excellent problem-solving skills and willingness to think outside the box.
- Experience with production software quality assurance practices, methodologies, and procedures
- Strong ownership of deliverables, Excellent communication skills and experience working with global teams.
Key Responsibilities :- Develop and execute validation plans for AI/ML compute stacks, including but not limited to HIP, CUDA, OpenCL, OpenVINO, ONNX Runtime, and TensorFlow/PyTorch integrations.
- Validate end-to-end AI pipelines, covering model conversion (e.g., PyTorch to ONNX), inference runtimes (e.g., ONNX Runtime, TensorRT, ROCm/HIP), compilers/toolchains (e.g., TVM, Vitis AI, XDNA, XLA), kernel execution, memory transfer, and inference results.
- Profile ML workloads to identify performance bottlenecks and areas for optimization.
- Develop and maintain robust Python automation scripts for validation test suites.
- Work within a Linux/Yocto environment.
- Collaborate with global teams to ensure product quality and a seamless software development lifecycle.
- Debug and troubleshoot complex issues related to AI/ML software.
Required Skills & Experience
- 3-6 years of experience in software validation or a related field.
- Strong background in machine learning fundamentals, including deep learning, large language models, and recommender systems.
- Proficiency in Python programming is a must.
- Extensive experience with Linux and Yocto.
- Hands-on experience with open-source frameworks like PyTorch, TensorFlow, and ONNX-Runtime.
- Experience with production software quality assurance practices, methodologies, and procedures.
- Excellent problem-solving skills and a proactive, ownership-oriented approach to deliverables.
- Strong communication and collaboration skills for working with global teams. (ref:hirist.tech)
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