← All roles

Senior Staff Engineer, ML Ops (R4941)

Shield AI· Hivemind Enterprise Division – Engineering
Apply on company site
San Mateo, California$280k - $420kFull Time EmployeePosted 1mo ago

About the role

Senior Staff Engineer to design and build the Kubernetes-native AI Factory Reference Architecture for training, evaluation, and deployment of modern AI systems across cloud, on-premise, sovereign, and air-gapped environments.

Responsibilities

  • 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.
  • Data & Model Lifecycle: Build platform capabilities that enable dataset management, experiment tracking, artifact management, model versioning, evaluation, deployment, monitoring, and continuous model improvement.
  • Platform Distribution: Develop repeatable deployment and lifecycle management solutions using Infrastructure as Code and modern platform engineering practices. Support commercial cloud, customer-managed infrastructure, sovereign environments, and fully air-gapped deployments.
  • Technology Leadership: Evaluate emerging AI infrastructure technologies and establish architectural patterns that balance scalability, performance, maintainability, and developer experience.
  • Cross-Functional Collaboration: Work closely with AI researchers, autonomy teams, infrastructure engineers, and product teams to ensure the platform evolves alongside customer needs and advances in AI.

Qualifications

  • Experience building Kubernetes-native AI or MLOps platforms supporting distributed machine learning workloads.
  • Deep understanding of modern AI training frameworks, including PyTorch, Hugging Face Transformers and distributed training techniques.
  • Experience operating GPU-accelerated infrastructure and distributed training systems.
  • Strong understanding of Kubernetes, Linux, networking, security, storage, and distributed systems.
  • Experience with GPU scheduling concepts and large-scale AI workloads.
  • Experience packaging and deploying cloud-native infrastructure using Terraform and Helm.
  • Strong software engineering skills in Python and Golang and modern cloud-native technologies.
  • Experience collaborating closely with ML researchers to translate research workflows into scalable platform capabilities.

Skills

Required:Kubernetes-native AI / MLOps platformPyTorchHugging Face TransformersGPU schedulingTerraform & HelmPythonGolang

Benefits

  • Pay within range listed + Bonus + Benefits + Equity
  • Temporary employee offer package (applicable after 60 days of employment) + temporary benefits package
  • Salary compensation influenced by skill set, experience, licenses/certifications, and location; background check may be required. Veterans/military fellows and part-time employees may have different eligibility.
Last updated Oct 23, 2026. Interested? Apply on the company site.

About Shield AI

Autonomy for the world.

Our mission is to protect service members and civilians with intelligent systems.

AerospaceAutonomyDefenseliquid-ai-recruiting-targetsetter-30setter-30-2026-q1
Company profileWebsite

More open roles at Shield AI