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Job Description Hello, Infrastructure Engineer - Software Engineer Infrastructure & Hardware Optimization - Remote We have below job opening. If you are interested and your experience match with job description. Please send your updated resume....Asap Software Engineer Infrastructure & Hardware Optimization Location: SF, CA, Portland, OR, Dallas, TX - Remote but need to be local of 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 agentic inference deployments. Ideal Experience: 47 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. Qualifications: Additional Information All your information will be kept confidential according to EEO guidelines.