CUDA

Torc Robotics

Full-time · Ann Arbor, MI · Remote

Lead the machine learning team building lidar and radar perception systems for autonomous trucks, managing both technical direction and people while balancing model performance against real-time compute constraints. Suits experienced ML managers comfortable with embedded systems complexity and collaborative cross-functional work.

Listed on Torc Robotics’s careers site · Apply there ↗

Crusoe

San Francisco, CA · $170,000 – $205,000

This role involves building CI/CD infrastructure and deployment automation for Crusoe's large-scale GPU cluster fleet across their AI cloud. You'll work on testing frameworks, configuration management, and orchestration systems that enable reliable releases across datacenters, requiring deep expertise in Linux, cloud infrastructure, and modern DevOps tooling.

Listed on Crusoe’s careers site · Apply there ↗

Modal

San Francisco, CA · $220,000 – $300,000

Modal is seeking a systems engineer to own the container runtime stack that powers inference and training workloads across their AI infrastructure platform. This role involves building low-level systems in Rust and Go, optimizing startup times and memory efficiency, and debugging complex interactions between Linux, containers, GPUs, and distributed systems.

Listed on Modal’s careers site · Apply there ↗

Deepgram

USA - Remote · $155,000 – $245,000

This role adapts Deepgram's speech AI models to run on non-GPU edge hardware and embedded platforms, handling quantization, operator substitution, and deployment automation to get production models onto customer devices with minimal changes. It suits an experienced engineer who has shipped models to constrained hardware and wants to own that process across many platforms.

Listed on Deepgram’s careers site · Apply there ↗

Menlo Ventures Portfolio

New York, NY · $350,000 – $850,000

This role optimizes Anthropic's inference engine—the software layer that manages how their Claude language model runs on accelerators and serves requests efficiently. It's ideal for systems engineers who enjoy performance optimization work across hardware, networking, and distributed systems.

Listed on Menlo Ventures Portfolio’s careers site · Apply there ↗

NVIDIA

Full-time · $184,000 – $287,500

This role leads the design and implementation of next-generation distributed storage infrastructure for NVIDIA's high-performance computing and AI workloads, requiring deep expertise in storage systems, Linux, and cloud-scale operations. It suits engineers with 8+ years building and optimizing large-scale storage solutions who want to influence the infrastructure powering GPU-accelerated computing at a major technology company.

Listed on NVIDIA’s careers site · Apply there ↗

KLA-Tencor

Full-time · Ann Arbor, MI · $105,900 – $180,000

This role designs and optimizes high-performance computing software for large-scale Linux clusters used in semiconductor manufacturing, requiring deep expertise in parallel computing, system-level performance tuning, and hardware-software co-design. It suits engineers with strong foundations in systems programming who want to work on mission-critical infrastructure that directly impacts production tools at scale.

Listed on KLA-Tencor’s careers site · Apply there ↗

Juniper Networks

Full-time · Bloomington, Minnesota, United States of America · $62,900 – $145,300

HPE is seeking an engineer to benchmark and optimize performance of their high-performance computing and AI systems, running tests on massive supercomputers and analyzing results to guide product development. This role suits someone with deep HPC systems knowledge, hands-on experience with parallel computing and GPU programming, and the drive to work on cutting-edge infrastructure problems.

Listed on Juniper Networks’s careers site · Apply there ↗

AeroVironment

Full-time · Huntsville, AL

This role develops and validates physics-based 3D synthetic environments for military simulation and testing, requiring deep expertise in radiometric rendering, graphics programming, and real-time systems integration. It suits experienced software engineers comfortable leading technical work on complex modeling systems within defense contracting.

Listed on AeroVironment’s careers site · Apply there ↗

Accenture

Lead the design and implementation of AI and machine learning platforms embedded in infrastructure management systems, architecting production-grade MLOps and GenAIOps solutions across cloud environments. This role suits experienced ML engineers who want to move into infrastructure automation and advisory work, combining deep technical expertise with client-facing strategy and mentorship.

Listed on Accenture’s careers site · Apply there ↗