38 years of experience in software development, AI/ML engineering, or system validation.
Strong programming skills in Python and C/C++.
Solid understanding of Linux, build systems, and debugging tools.
Hands-on experience with AI frameworks such as PyTorch, TensorFlow, or ONNX Runtime.
Experience running and debugging AI models on GPU-accelerated systems.
Strong background in machine learning fundamentals, including deep learning,large language models, and recommender systems.
Strong background in validation, defect and software development life cycle
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 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
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 team.
Looking for an experienced Software Developer to automate robotics stack tests and workflows.
Design and maintain Python-based test frameworks for simulation, integration, and hardware-in-the-loop (HIL).
Develop endtoend automation for build, test, and deploy workflows in CI/CD environments.
Create scalable pipelines for regression testing, scenario-based simulations, and performance validation.
Implement tools for log analysis, metric collection, triage automation, and failure diagnostics.
Work closely with robotics dev, QA, and DevOps teams to ensure test reliability and reproducibility.
Build reusable libraries, automation utilities, and internal developer tools.
Strong expertise in Python, Linux, shell scripting, and Git workflows.
