Senior Staff Engineer, ML Ops (R4941)

Shield AI
San Mateo
Workplace: OnsiteFull timeUSD 280,000 - 420,000 annuallyFunction: Solutions Engineering & Sales EngineeringSkills: ["Cross-functional collaboration","Technology leadership","Software engineering"]

Build and lead Shield AI’s AI Factory Reference Architecture, a Kubernetes-native platform for developing, training, evaluating, and deploying modern AI models. Partner with ML researchers and autonomy teams to convert evolving research workflows into scalable platform capabilities across distributed training, simulation, and inference. Own GPU infrastructure, orchestration/scheduling, data and model lifecycle tooling, and repeatable deployments via infrastructure-as-code for cloud, on-prem, sovereign, and air-gapped environments.

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FursaFursa
Shield AI
Shield AI
5 days ago

Senior Staff Engineer, ML Ops (R4941)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 16 hours agoStatus: Live

Job Summary

Build and lead Shield AI’s AI Factory Reference Architecture, a Kubernetes-native platform for developing, training, evaluating, and deploying modern AI models. Partner with ML researchers and autonomy teams to convert evolving research workflows into scalable platform capabilities across distributed training, simulation, and inference. Own GPU infrastructure, orchestration/scheduling, data and model lifecycle tooling, and repeatable deployments via infrastructure-as-code for cloud, on-prem, sovereign, and air-gapped environments.
Location: San Mateo
Workplace: Onsite
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Mid level

Key Responsibilities

  • •Design and implement the AI Factory Reference Architecture as a Kubernetes-native platform for distributed training, simulation, evaluation, and deployment.
  • •Partner with ML researchers to support evolving training workflows and state-of-the-art AI frameworks, including reinforcement learning and emerging research workflows.
  • •Develop distributed AI infrastructure for training, simulation, inference, and reinforcement learning workloads, including orchestration, scheduling, and resource management.
  • •Design and optimize shared GPU infrastructure across cloud and on-prem environments, improving utilization, scheduling, storage/networking, observability, and reliability.
  • •Build platform capabilities for the data and model lifecycle (datasets, experiment tracking, artifacts, versioning, evaluation, monitoring, and continuous improvement) and enable repeatable deployments using infrastructure as code across cloud, customer-managed, sovereign, and air-gapped environments.

Pay and Benefits

Salary: USD 280,000 - 420,000 annually
Perks:Annual BonusEquity

Key Requirements

  • •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 packaging and deploying cloud-native infrastructure using Terraform and Helm.
Skills:Cross-functional collaborationTechnology leadershipSoftware engineering
Tech Stack:KubernetesLinuxPythonGolangPyTorchHugging Face TransformersTerraformHelmRaySlurmOpenTelemetryPrometheusGrafana

Company Brief

Shield AI
Develops AI-powered autonomy and software for military aircraft and drones to enable autonomous ISR and combat missions, integrating perception, navigation, and mission planning for defense customers.
Industry: Defense Technology
Company Size: Large (251 to 1,000 employees)
Growth: Scaleup
Funding: Series E+
Headquarters: San Diego, United States
Founded: 2015
WebsiteLinkedIn