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Get AI-powered advice on this job and more exclusive features. Job Description Hello, Infrastructure Engineer - Software Engineer – Infrastructure & Hardware Optimization - Remote We have the following job opening: If you are interested and your experience matches the job description, please send your updated resume as soon as possible. Software Engineer – Infrastructure & Hardware Optimization Location: SF, CA, Portland, OR, Dallas, TX - Remote but need to be local to the respective location Duration: 6 Months+ Contract Job Description: We are seeking a skilled low-level systems engineer to join the team. This individual will focus on infrastructure software that detects, configures, and optimizes AI inference pipelines across heterogeneous hardware accelerators (e.g., NVIDIA / AMD GPUs, TPUs, AWS Inferentia, FPGAs). You will work on hardware abstraction layers, containerized runtime environments, benchmarking, telemetry, and driver orchestration logic for multi-cloud agent inference deployments. Ideal Experience: 4–7 years experience in systems software or infrastructure engineering, preferably with exposure to AI/ML workloads. Deep expertise in CUDA, NCCL, ROCm, or other accelerator programming frameworks. Familiarity with LLM inference runtimes (TensorRT-LLM, vLLM, ONNXRuntime). Experience with Kubernetes scheduling, device plugin development, and runtime patching for heterogeneous compute. Strong Python/C++ and Linux systems programming skills. Passion for building scalable, portable, and secure AI infrastructure. Responsibilities:

Design and implement cross-platform hardware detection systems for GPUs/TPUs/NPUs using CUDA, ROCm, and low-level runtime interfaces. Build and maintain plugin-based infrastructure for capability scoring, power efficiency tuning, and memory optimization. Develop hardware abstraction layers (HAL) and performance benchmarking tools to optimize AI agents for cloud-native inference. Extend container-based MLOps systems (Docker/Kubernetes) with support for hardware-specific runtime containers (e.g., TensorRT, vLLM, ROCm). Automate driver validation, container security hardening, and runtime health monitoring across deployments. Integrate telemetry systems (Prometheus, Grafana) to surface per-device inference performance metrics and health status. Collaborate with solutions and DevOps teams to ensure hardware-aware agent deployment across cloud providers. Additional Information All your information will be kept confidential according to EEO guidelines. Seniority level

Not Applicable Employment type

Contract Job function

Information Technology Industries

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