Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Responsible for starting up, developing and optimizing processes to improve product quality and reliability, working on process yield improvement, cost reduction, productivity improvement and risk management as well as resolving manufacturing line problems. Identify, diagnose and resolve assembly process related problems by applying failure analysis, FMEA, 8D or SPC/FDC methodology. Handle new process baseline qualifications and managing. Identify, diagnose and resolve assembly process related problems. Coordinate and execute process, equipment and material evaluation and optimization initiatives and implement changes at process step. Lead and participate in continuous yield improvement and cost reduction activities. Validate and fan out new process baseline qualified, including new processes, tools and materials for new product introduction. Support site to site portability. Manage and audit material suppliers to achieve quality, cost and risk management objectives. Support internal and external audits. Develop new or modified process formulations, define processing or handle equipment requirements and specifications, and review processing techniques and methods applied in the manufacture, fabrication, and evaluation of products. Coordinate design requirement review with appropriate engineering/scientific personnel to ensure compatibility of processing methods. Compile and evaluate test data to determine appropriate limits and variables for process or material specifications. Plan projects involving definition and selection of new concepts, equipment automati
Market pay estimate
$240,050–$298,228 / year for comparable Engineering Manager roles in United States. Not employer-provided.
Role overview
Job description
NVIDIA's invention of the GPU transformed computer graphics, parallel computing, and modern AI. Today, NVIDIA high-performance processing platforms power breakthroughs across generative AI, autonomous systems, scientific computing, robotics, and high-performance data centers.
NVIDIA's compiler technologies are key enablers of AI at scale, turning rapidly evolving deep learning models into highly optimized GPU programs for training and inference. As AI models, GPU architectures, and compiler systems become more sophisticated, AI compiler quality has become a deep technical challenge at the intersection of compilers, machine learning frameworks, numerical computing, formal reasoning, and large-scale systems engineering. To address these complex challenges, we are seeking an Engineering Manager to spearhead our strategy for verifying AI compilers built for next-generation deep learning workloads. This is a hands-on compiler engineering leadership role for someone who understands where compiler quality can regress in modern AI compiler stacks.
What You'll Be Doing:
Lead, mentor, and grow a highly technical team responsible for AI compiler verification.
Own the verification of next-generation AI workloads, including LLMs and agentic AI systems, across the full spectrum of the AI compiler stack and execution pipeline.
Define formal-verification requirements for AI compiler transformations and generated GPU programs, including formal specifications, tensor/operator semantics, semantic preservation, code equivalence, numerical behavior, and properties stressed by AI-generated or adversarial workloads.
Drive the use of AI-assisted and compiler-aware verification techniques, including adversarial workload generation, differential testing, symbolic reasoning, formal methods, fuzzing, static analysis, and automated debugging.
Partner closely with AI compiler development, CUDA software, ML framework, runtime, product, and AI software teams to build scalable verification infrastructure, improve engineering velocity, and increase production confidence.
What We Need To See:
BS, MS, or PhD in Computer Science, Computer Engineering, or a related field, or equivalent experience.
10+ overall years of total relevant software engineering experience, including at least 3 years experience leading engineering teams or major technical initiatives.
Experience with AI compiler or framework technologies such as MLIR, TensorRT, XLA, Triton, PyTorch, or JAX.
Fluency with AI workload and ML framework concepts, including computation graphs, tensor operations, model execution, and training or inference workflows.
Strong people management skills, including hiring, mentoring, performance management, and team development.
Ways To Stand Out From The Crowd:
Hands-on with deep learning compiler internals, including compiler IRs, optimization and lowering pipelines, code generation, runtime integration, or production compiler infrastructure.
Experience verifying performance-sensitive compiler behavior and root-causing subtle regressions in production AI/ML systems using computational methods, fuzzing, code inspection, or automated debugging.
Background in formal verification or programming languages, with familiarity in formal specifications, theorem proving, Lean, SMT/SAT solvers, or symbolic reasoning.
With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 270,250 USD for Level 2, and 200,000 USD - 322,000 USD for Level 3.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Role market pulse
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What they are looking for
Skills & requirements
Qualification
What We Need To See: BS, MS, or PhD in Computer Science, Computer Engineering, or a related field, or equivalent experience
Hiring company
NVIDIA
We create the world’s fastest supercomputer and largest gaming platform.
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