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Systems Software Engineer
Systems Software Engineer at Quadric building the low-level stack for its General-Purpose Neural Processing Unit (GPNPU) edge-AI chip — owning components like the instruction set simulator, loader/assembler, remote debugger, and C++ host/device APIs. Work is heavily modern C++, done in close co-design with the hardware team.
HPC Systems Engineer
Builds and expands Linux-based HPC simulation clusters (Slurm/PBS schedulers, BeeGFS/NFS storage, InfiniBand, NVIDIA GPUs) powering CFD/FEA propulsion analysis, while serving as IT's enterprise Linux SME — automating with Python/Bash/Ansible/Terraform and hardening to NIST 800-171/CMMC Level 2. Hybrid role in Longmont, CO.
Senior Software Engineer - Performance Tooling
Senior engineer on Microsoft's AI Frameworks team building performance tooling: benchmarking, profiling, and optimizing OpenAI/LLM training and inference across the AI software stack (compilers, runtimes, libraries) on GPUs and Microsoft hardware. Core tech: C++, Python, CUDA, PyTorch/ONNX Runtime, GPU profiling.
Software Engineer: Perception (I)
Early-career Software Engineer (Perception) joining Lodestar's perception and machine vision team to build and optimize computer vision and ML models that detect, classify, and track unknown space targets in real time for the MITHRIL autonomous spacecraft platform. Core stack includes Python, C++, OpenCV, and GPU/edge optimization tools like CUDA and TensorRT.
Software Engineer - Simulations (I,II,III)
Lodestar (Los Angeles) is hiring Software Engineers I-III to build the simulation environment for MITHRIL, its autonomous spacecraft-protection system. Day to day you develop high-fidelity sensor and environment models in Unreal Engine, stand up SIL/HIL test benches, and design distributed simulation services using C++, Python, and ROS 2.
AI Engineer
Build and deploy production-grade AI systems for edge environments like offshore platforms, mines, and autonomous vehicles, optimizing models for latency, robustness, and security across disconnected settings.
Member of Technical Staff
AI infrastructure engineer on a small team optimizing large language model inference end to end — tuning open-source model serving (batching, KV cache, quantization, speculative decoding), writing CUDA/HIP/Triton GPU kernels, and operating multi-vendor accelerator clusters. On-site in San Francisco; $200k-$300k with visa sponsorship.