Staff AI/ML Validation Engineer, AMD

Telangana, India, Hyderabad
March 16, 2026
Full Time

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Job Description

AMD is hiring a Staff AI/ML Validation Engineer to test and optimize AI and GPU systems, ensuring functional correctness, scalability, and efficiency. The role collaborates with architecture, firmware, and software teams, develops automated testing, investigates performance issues, and provides insights to guide design decisions in a global engineering environment.

Date Posted: February 2026

Expiration Date: NA

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Main Duties

  • Process for GPU compute and AI workloads which include ML, DL and HPC pipelines needs your complete leadership. 
  • Advanced debugging capabilities to investigate and solve intricate problems across all hardware components and firmware and driver and runtime and operating system environments. 
  • Conducts performance analysis and makes optimization improvements to all computing units and memory bandwidth and cache systems and interconnect architectures. 
  • Automation tools and frameworks through Python development to enhance validation coverage while increasing efficiency. 
  • Together with different global teams to shape architectural choices while making sure products meet their readiness criteria.

Essential Qualifications

  • Educational qualifications include a Bachelor’s degree or a Master’s degree in Computer Engineering, Electrical Engineering, or a closely related technical discipline.
  • Accumulated eight years or more of professional experience in GPU computing, AI testing, system debugging, and performance engineering.
  • Knowledge about GPU systems, parallel processing architectures, and artificial intelligence and machine learning execution patterns.
  • Demonstrates expertise in programming and automation through their proficiency in Python and their ability to implement continuous integration and continuous deployment systems.
  • Linux and Windows operating systems, performance analysis techniques, and profiling tools for system software assessment.

Preferred Qualifications

  • Experience with ROCm and other GPU compute stacks and AI accelerator platforms.
  • Knowledge about compiler optimization and runtime optimization methods which are relevant to AI workload processing, training and inference systems. 
  • Applicants should have knowledge about power consumption and thermal management and reliability testing of GPU systems. 
  • Experience in designing hardware and software systems or working in large-scale product development projects. 

Demonstrated their ability to lead through mentoring technical staff and conducting design evaluations and working with different teams.

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