Hiring: Senior Staff Engineer, ML Ops (R4941) Company: Shield AI Location: San Mateo, CA Job Posted Time: 2026-09-03 10:33:14 Employment Type: Full-time Target Skills & Keywords : AI, Go, Grafana, Helm, Hugging Face, Infrastructure as Code, Kubernetes, Linux, MLOps, Machine Learning, OpenTelemetry, Prometheus, PyTorch, Python, Reinforcement Learning, Terraform, Transformers About the job Required Skills: •Shield AI builds autonomy systems for defense applications, including air, maritime, and space platforms operating in complex and contested environments. •The AI Factory serves two purposes. Internally, it powers autonomy development across Hivemind and other AI programs. Externally, it becomes the reference architecture deployed into customer environments, spanning commercial cloud, on-premise infrastructure, sovereign deployments, and fully air-gapped systems. •Success in this role requires balancing researcher productivity, platform simplicity, operational excellence, and long-term maintainability. You will work hands-on across the stack, helping shape both the platform architecture and its implementation while staying closely aligned with the rapidly evolving AI ecosystem. •AI Platform Development: Lead the design and implementation of the AI Factory Reference Architecture, delivering a Kubernetes-native platform for AI development, distributed training, simulation, evaluation, and deployment. •AI Research Enablement: Partner directly with ML researchers to understand evolving training workflows and ensure the platform supports state-of-the-art AI frameworks, foundation model development, reinforcement learning, distributed training, and emerging research workflows. •Developer Experience: Design self-service AI development workflows that enable engineers to move seamlessly from local experimentation to large-scale distributed execution using familiar open source tools and frameworks. •Distributed AI Infrastructure: Build the infrastructure required to support distributed training, simulation, inference, and reinforcement learning workloads. Evaluate and integrate orchestration, scheduling, and resource management technologies to maximize scalability and developer productivity. •Compute Platform: Design and optimize shared GPU infrastructure across cloud and on-premises environments. Improve resource utilization, scheduling efficiency, storage, networking, observability, and overall platform reliability. Qualifications: •Comprehensive expertise in modern AI training frameworks, including PyTorch, Hugging Face Transformers and distributed training techniques. •In-depth knowledge of Kubernetes, Linux, networking, security, storage, and distributed systems. •Strong software engineering skills in Python and Golang and modern cloud-native technologies. Compensation: •$280,000 - $420,000 / year •Pay within range listed + Bonus + Benefits + Equity Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!