Staff ML Engineer, Autonomy & Planning (Robotics)

Location: Full-time, on-site at Sunnyvale HQ, Sunnyvale, California, United States

Base salary: $240,000–$275,000 per year. Equity is provided through stock options.

Company

hirify.global is a security technology company developing autonomous machines, AI-driven software, and managed security services.

What you will do

• Architect and ship the full intelligence-to-action loop for a deployed production fleet of autonomous robots.
• Advance machine learning for embodied autonomy, including computer vision, learned planning, open-world generalization, and real-time decision making.
• Integrate vision-language-action models to improve robot reasoning, situational understanding, and explainability in safety-critical environments.
• Build a closed-loop learning pipeline using production outcomes and operator feedback for model evaluation and policy improvement.
• Drive architecture decisions across the autonomy stack and mentor engineers across perception, planning, and controls.

Requirements

• 7+ years of experience shipping autonomy, planning, or decision-making systems to production in robotics, autonomous vehicles, or safety-critical platforms.
• Deep expertise in behavior planning, policy execution, imitation learning, reinforcement learning, end-to-end learned autonomy, or large-scale ML for real-time decision making.
• Hands-on experience integrating learned planning or policy models with classical control systems and deterministic safety constraints.
• Strong software engineering skills in C++ and Python, with experience in real-time autonomy stacks.
• Experience taking systems from research prototypes to deployed production platforms and driving architecture decisions across perception, planning, and controls.

Nice to have

• MS or PhD in Robotics, Computer Science, Machine Learning, or a related field.
• Experience with autonomous vehicles, deployed robotics, or embodied AI systems in production.
• Experience with trajectory planning, behavior modeling, autonomy policy design, VLA architectures, or foundation models for robot control.
• Experience building data flywheel or simulation-based training pipelines for production ML systems.
• Familiarity with functional safety standards, ISO 26262, or SOTIF.

Culture & Benefits

• Work on autonomous machines and AI-driven software for security applications.
• Medical, dental, and vision benefits.
• 401(k) plan and paid time off.
• Stock options.