Driver Engineer, AI Accelerator Stack (Remote)

Modular; United States; Hybrid; USD 167,000 - 242,000; Full time

Benefits offered by this job

Open-source project

On-site in Los Altos, CA

Travel 2-4 times/year

Competitive compensation

Great benefits

Job summary

Modular is seeking a Driver Engineer to join its team improving the low-level infrastructure between the compiler and runtime stack across NVIDIA, AMD, Apple Silicon, and other accelerators. You will help design device abstractions, manage asynchronous execution, memory allocation, and cross-platform driver interfaces, enabling high performance and portability for MAX and Mojo.

You will collaborate with Kernels, Graph Compiler/Runtime, Serving, and Mojo library teams, contribute to open-source

Qualifications

• 3+ years of experience developing high-performance, low-latency production systems software in modern C++ (C++17/20).
• Strong systems programming fundamentals around ownership, lifetimes, concurrency, multithreading, synchronization, memory management, and parallel execution.
• Hands-on experience with at least one accelerator driver-level API (CUDA Driver API, HIP, Metal, Vulkan compute).
• Practical understanding of accelerators: devices, contexts, streams/queues, events, synchronization, module loading, kernel launch, and host/device interaction.
• Working knowledge of accelerator execution and memory models, including stream ordering, asynchronous execution, host-device transfers, and pinned memory.
• Experience designing and maintaining APIs used by other engineers with good ergonomics and compatibility.
• Strong debugging skills in asynchronous and concurrent systems; diagnosing race conditions, resource lifetimes, memory issues, and cross-boundary failures.
• Experience with systems debugging tools such as GDB, LLDB, sanitizers.

Responsibilities

• Design, implement, and extend core driver abstractions — including Device, Context, Queue, Memory, and Function — across diverse hardware backends.
• Build clean abstractions around vendor driver APIs while exposing hardware-specific functionality where needed for performance or advanced capabilities.
• Develop infrastructure for asynchronous execution, including queues, streams, events, synchronization, resource lifetimes, and error propagation.
• Build and improve memory-management infrastructure spanning device allocation, host/device transfers, pinned memory, asynchronous allocation, and other accelerator memory-management capabilities.
• Contribute to multi-accelerator and multi-node communication and collective primitives underpinning large-model inference.
• Work with high-performance interconnect and networking technologies (NVLink, RDMA, InfiniBand, RoCE, EFA, sockets, UCX) where relevant.
• Improve diagnostics, observability, and error reporting across the asynchronous execution stack.
• Debug difficult correctness and reliability issues involving concurrency, synchronization, memory lifetimes, device state, resource leaks, and asynchronous execution.
• Partner with Kernels, Graph Compiler/Runtime, Serving, and Mojo library teams to refine driver and runtime surfaces.
• Ensure driver abstractions remain performant and maintainable as Modular expands to more accelerator architectures.
• Participate in architecture discussions, code reviews, and collaborative software development to maintain high engineering bar.
• Contribute to our fully open-source project and public codebase.

Skills

C++17/20

Systems programming

Multithreading

Asynchronous execution

Memory management

Device/Context/Queue concepts

Debugging asynchronous systems

Tools

CUDA Driver API

HIP

Metal

Vulkan compute

GDB

LLDB

Sanitizers

Job description

Modular is seeking a Driver Engineer to join its team improving the low-level infrastructure between the compiler and runtime stack across NVIDIA, AMD, Apple Silicon, and other accelerators. You will help design device abstractions, manage asynchronous execution, memory allocation, and cross-platform driver interfaces, enabling high performance and portability for MAX and Mojo.

You will collaborate with Kernels, Graph Compiler/Runtime, Serving, and Mojo library teams, contribute to open-source