SEMI LEAF is hiring an experienced AI/ML Validation Engineer! Drive quality assurance for advanced AI systems, tackle complex validation challenges, and grow in a high-impact role offering 15-25 LPA. Ideal for professionals with 5+ years in ML model testing.
Table of Contents
Job Title: AI/ML Validation Engineer
Location: India
Job Type: Full Time
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About the job
This job is sourced from a job board. Learn More
Required Skills
Strong ownership of deliverables, Excellent communication skills, and experience working with global teams
Strong background in machine learning fundamentals, including deep learning, large language models, and recommender systems.
Strong background in validation, defect, and the software development life cycle
Strong knowledge of Ubuntu / Yocto Linux
Experience working with open-source 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 example, 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
How to Apply:
Please submit your resume and cover letter through Submit Resume to apply for this position.
Apply Here
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Q1: What’s the salary range for SEMI LEAF’s AI/ML Validation Engineer role?
A: Selected candidates earn ₹15-25 LPA based on experience, with bonuses for expertise in tools like TensorFlow Validator or MLflow.
Q2: Is 5 years of experience mandatory for this position?
A: Yes. SEMI LEAF requires 5+ years in AI/ML validation, including hands-on work with model testing frameworks (e.g., Seldon, Great Expectations) and regulatory standards (ISO/IEC 25010).
