Staff Software Engineer, Perception (r5421)

Shield AI Shield AI · Defense · Washington, DC +3 · Flight System Integration

Staff Software Engineer focused on perception for autonomous defense systems, combining ML and computer vision. The role involves developing vision, VLM, and VLA models, building data pipelines, SFT workflows, evaluation frameworks, and deployment infrastructure. It bridges AI research with production systems, influencing model adaptation, evaluation, and deployment.

What you'd actually do

  1. Lead the technical development of advanced machine learning solutions that define the future of perception for autonomous systems.
  2. Own the team's most challenging technical problems, drive architecture and model development across multiple efforts, and influence how foundation models are adapted, evaluated, and deployed for real-world autonomy.
  3. Working closely with researchers, perception engineers, autonomy engineers, and platform teams, you'll bridge cutting-edge AI research with scalable production systems while mentoring engineers and raising the technical bar across the organization.

Skills

Required

  • Machine Learning
  • Computer Vision
  • Vision-Language Models (VLM)
  • Vision-Language-Action Models (VLA)
  • Data Pipelines
  • Supervised Fine-Tuning (SFT)
  • Evaluation Frameworks
  • Deployment Infrastructure
  • Foundation Model Adaptation
  • Software Engineering
  • Architecture Design
  • Mentoring

Nice to have

  • Autonomous Systems
  • Defense Technology

What the JD emphasized

  • state-of-the-art machine learning
  • vision-language (VLM), and vision-language-action (VLA) models
  • supervised fine-tuning (SFT) workflows
  • evaluation frameworks
  • deployment infrastructure
  • foundation models are adapted, evaluated, and deployed

Other signals

  • Develops perception capabilities for autonomous systems
  • Builds data pipelines, SFT workflows, evaluation frameworks, and deployment infrastructure
  • Transforms AI research into reliable, mission-ready perception capabilities
  • Leads technical development of ML solutions
  • Owns challenging technical problems, drives architecture and model development
  • Adapts, evaluates, and deploys foundation models for real-world autonomy