Cambridge, England, GB
Open 5 months, first seen by us 177 days agoEmployment type in the employer’s posting: FULL_TIMEFrom the employer’s posting
Build and maintain high-performance runtime and compiler components for end-to-end inference optimization
Define and implement mappings of large-scale inference workloads onto NVIDIA's systems
Benchmark and profile to ensure efficient mapping of neural network graphs to inference hardware
Prototype new compilation and runtime techniques for spatial processors
Work with hardware architects to feed back software observations and codesign features
Build, develop, and maintain high-performance runtime and compiler components, focusing on end-to-end inference optimization.
Define and implement mappings of large-scale inference workloads onto NVIDIA’s systems.
Benchmark, profile, and monitor key performance and efficiency metrics to ensure the compiler generates efficient mappings of neural network graphs to our inference hardware.
Prototype and evaluate new compilation and runtime techniques, including graph transformations, scheduling strategies, and memory/layout optimizations tailored to spatial processors.
Collaborate closely with hardware architects and design teams to feedback software observations, influence future architectures, and codesign features that unlock new performance and efficiency points.
What we need to see: * MS or PhD in Computer Science, Electrical/Computer Engineering, or related field, or equivalent experience, with 6 years of relevant experience. * Strong software engineering background with proficiency in systems level programming (e.g., C/C++ and/or Rust) and solid CS fundamentals in data structures, algorithms, and concurrency.
Open 5 monthsWe first saw this posting 177 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
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Day 177
Up longer than most. Similar jobs usually come down between day 6 and day 70.
Well past NVIDIA’s usual: its jobs come down by about day 36.
From 4,495 similar postings that came down, and 92 of NVIDIA’s. Coming down is not always a hire.
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* MS or PhD in Computer Science, Electrical/Computer Engineering, or related field, or equivalent experience, with 6 years of relevant experience. * Strong software engineering background with proficiency in systems level programming (e.g., C/C++ and/or Rust) and solid CS fundamentals in data structures, algorithms, and concurrency. * Hands on experience with compiler or runtime development, including IR design, optimization passes, or code generation.
* Experience with LLVM and/or MLIR, including building custom passes, dialects, or integrations. * Familiarity with deep learning frameworks such as TensorFlow and PyTorch, and experience working with portable graph formats such as ONNX. * Solid understanding of parallel and heterogeneous compute architectures, such as GPUs, spatial accelerators, or other domain specific processors.
Complete your application on jobs.nvidia.com. The employer’s form will show what is required.
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Yes. We’ve followed 2 other Senior Machine Learning Applications and Compiler Engineer, LPX jobs there since May 2026. All 2 are still up.
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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Cambridge, England, GB
* Experience with large-scale AI distributed inference or training systems, including performance modeling and capacity planning for multi rack deployments. #LI-Hybrid
No clear work-authorization passage found. Eligibility is unconfirmed.