NVIDIA · 11 hours ago
Senior Machine Learning Applications and Compiler Engineer
United States
Full-time
Remote
Senior Level
$152K/yr - $242K/yr
5+ years expNVIDIA is seeking engineers to develop algorithms and optimizations for their inference and compiler stack. The role involves working at the intersection of large-scale systems, compilers, and deep learning, focusing on optimizing neural network workloads for NVIDIA platforms.
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Responsibilities
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
Extend and integrate with NVIDIA’s SW ecosystem, contributing to libraries, tooling, and interfaces that enable seamless deployment of models across platforms
Benchmark, profile, and monitor key performance and efficiency metrics to ensure the compiler generates efficient mappings of neural network graphs to our inference hardware
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
Prototype and evaluate new compilation and runtime techniques, including graph transformations, scheduling strategies, and memory/layout optimizations tailored to spatial processors
Publish and present technical work on novel compilation approaches for inference and related spatial accelerators at top tier ML, compiler, and computer architecture venues
Qualification
Required
MS or PhD in Computer Science, Electrical/Computer Engineering, or related field, or equivalent experience, with 5 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
Strong analytical and debugging skills, with experience using profiling, tracing, and benchmarking tools to drive performance improvements
Excellent communication and collaboration skills, with the ability to work across hardware, systems, and software teams
Preferred
Ideal candidates will have direct experience with MLIR based compilers or other multilevel IR stacks, especially in the context of graph based deep learning workloads
Prior work on spatial or dataflow architectures, including static scheduling, pipeline parallelism, or tensor parallelism at scale
Contributions to opensource ML frameworks, compilers, or runtime systems, particularly in areas related to performance or scalability
Demonstrated research impact, such as publications or presentations at conferences like PLDI, CGO, ASPLOS, ISCA, MICRO, MLSys, NeurIPS, or similar
Experience with large-scale AI distributed inference or training systems, including performance modeling and capacity planning for multi rack deployments
Benefits
Equity
Benefits
Company
NVIDIA
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI.
10001+ employees
H1B Sponsorship
NVIDIA has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
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2025 (1877)
2024 (1355)
2023 (976)
2022 (835)
2021 (601)
2020 (529)
Funding
Current Stage
Public CompanyTotal Funding
$4.09BKey Investors
ARPA-EARK Investment ManagementSoftBank Vision Fund
2023-05-09Grant· $5M
2022-08-09Post Ipo Equity· $65M
2021-02-18Post Ipo Equity
Leadership Team
Jensen Huang
Founder and CEO
Michael Kagan
Chief Technology Officer
Recent News
Straits Times
2026-02-05
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