Working at Modular will enable you to grow quickly as you work alongside incredibly motivated and talented people who have high standards, possess a growth mindset, and a purpose to truly change the world. The estimated base salary range for this role to be performed in the US, regardless of the state, is $198,000.00 - $286,000.00 USD. The estimated base salary range for this role to be performed in Canada, regardless of the province, is $194,000.00 - $280,000.00 CAD. The salary for the successful applicant will depend on a variety of permissible, non-discriminatory job-related factors, which include but are not limited to education, training, work experience, business needs, or market demands. This range may be modified in the future. The total compensation for a candidate will also include annual target bonus, equity, and benefits, with equity making up a significant portion of your total compensation. For candidates who fall outside of the listed requirements, we nevertheless encourage you to apply as we may have openings that are lower/higher level than the ones advertised.
Driver Engineer
Location
United States + 1 moreAll locations: United States | Canada
Posted
2 days ago
Salary
$167K - $286K / year
Seniority
Mid Level
Job Description
Driver Engineer
Modular
Role Description As a Driver Engineer, you'll work on the layer that sits between Modular's compiler and runtime stack and the silicon — the devices, contexts, queues, synchronization primitives, memory allocators, networking, and collectives that every kernel and graph execution depends on. Your work directly affects how reliably and efficiently MAX and Mojo run across NVIDIA, AMD, Apple Silicon, and emerging accelerators, and how cleanly kernel and graph authors can target them from Mojo and Python. This is the team that makes "it just works on a new accelerator" actually true. LOCATION: Candidates based in the US or Canada are welcome to apply. You can work in our office in Los Altos, CA or remotely from home. What you will do - Implement and extend core driver abstractions — Device, Context, Queue, Memory, Function (kernel representation and launch) — across diverse hardware backends, including bindings that expose vendor-specific functionality where it matters. - Contribute to multi-accelerator and multi-node communication and collectives primitives that underpin large-model inference, using technologies like NVLink, RDMA (Infiniband, RoCE, EFA), and sockets — via a combination of direct programming and broker libraries like UCX. - Improve diagnostics and error reporting across our asynchronous execution stack — turning low-level driver failures into actionable messages for kernel and graph authors in production environments. - Partner with peer teams — Kernels, Graph Compiler/Runtime, and Serving — to build and refine the surfaces they consume in the Mojo standard library and MAX framework. - Participate in design discussions, code reviews, and collaborative software development to uphold high engineering standards. - Contribute to a fully open source project — everything you build will be public and part of our GitHub repo. Qualifications - 3+ years of experience writing high-performance, low-latency production systems C++ (modern C++17/20), with strong instincts for ownership, lifetime, ABI stability, concurrency, and parallelism. - Hands-on experience with at least one accelerator driver-level API — CUDA Driver API, HIP, Metal, or Vulkan compute — including streams, events, contexts, and module loading. Familiarity with async allocators and IPC is a plus. - Working understanding of accelerator execution and memory models — stream ordering, host↔device transfers, and pinned memory. Exposure to peer access and multi-GPU topologies (NVLink/xGMI, NUMA) is a plus. - Solid instincts for library and API design — naming, layering, ergonomics. - Strong debugging skills in asynchronous, multi-device systems — GDB/LLDB, sanitizers, CUDA/HIP error modes, race conditions, leaked resources. - A proactive, collaborative mindset, intellectual curiosity, and drive to identify and solve complex technical challenges as part of a high-performing team. Requirements - Experience with asynchronous runtimes, custom memory allocators, or RDMA-based networking (Infiniband, RoCE, EFA, UCX, NIXL, MPI, NVSHMEM/ROCSHMEM/OpenSHMEM) is helpful but not required. - Exposure to non-NVIDIA accelerators in production — AMD ROCm, Apple Metal, etc. - Experience with zero-copy tensor interoperability — DLPack, the CUDA Array Interface, or similar. - Familiarity with Mojo, or recent open-source contributions to systems projects (LLVM, PyTorch, JAX/XLA, TVM, IREE, vLLM, TRT-LLM). - An advanced degree in Computer Science or a related field. Benefits - Amazing Team: We are a progressive and agile team with some of the industry’s best engineering and product leaders. - World-class Benefits: Premier insurance plans, up to 5% 401k matching, flexible paid time off, and more are available to you! - Competitive Compensation: We offer very strong compensation packages, including stock options. - Team Building Events: We organize regular team onsites and local meetups in Los Altos, CA as well as different cities. Traveling 2-4 times a year is expected for all roles. The estimated base salary range for this role to be performed in the US, regardless of the state, is $167,000.00 - $286,000.00 USD. The estimated base salary range for this role to be performed in Canada, regardless of the province, is $158,000.00 - $270,000.00 CAD. The salary for the successful applicant will depend on a variety of permissible, non-discriminatory job-related factors, which include but are not limited to education, training, work experience, business needs, or market demands. This range may be modified in the future. The total compensation for a candidate will also include annual target bonus, equity, and benefits, with equity making up a significant portion of your total compensation. For candidates who fall outside of the listed requirements, we nevertheless encourage you to apply as we may have openings that are lower/higher level than the ones advertised.
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