Staff ML Engineer, Autonomy & Planning

Job Description

Salary: $240,000 to $275,000 DOE

AboutKnightscope

Knightscope is a security technology company building the nations first Autonomous Security Force. The Company combines autonomous machines, advanced software, and human expertise to help protect people, property, and critical infrastructure. Knightscopes long-term mission is to make the United States of America the safest country in the world.

About the Role

The gap between a robot thatobservesand a robot that acts is the intelligence layer. We are looking for a Staff Autonomy Engineer to own thislayerend to end. You will define how ourrobots reasonabout their environment and respond, drawing on the latest advances in embodied AI, learned planning, and real-time decision making. This is not a role where you own one slice of a large stack. You will architect and ship the full intelligence-to-action loop on a deployed productionfleet andbuild the learning pipeline that makes it better with every mission.

Key Responsibilities

Advance core AI and machine learning capabilities for embodied autonomy, spanning computer vision, learned planning, open-world generalization, and real-time decision making, across deployed robotic platforms.

Push the boundaries of learning-based robotics by incorporating large vision-language-action models to improve reasoning, situational understanding, and explainability in safety-critical environments.

Own the full intelligence-to-action loop: from sensor observations through entity reasoning, world-state modeling, to policy decisions that drive safe, bounded robot behavior.

Build the closed-loop learning pipeline: production outcomes and operator feedback feed model evaluation and policy improvement withoutmodifyingsafety-critical boundaries.

Drive technical architecture decisions across the autonomy stack and mentor engineers across the team.

Required Qualifications

7+ years shipping autonomy, planning, or decision-making systems to production in robotics, autonomous vehicles, or safety-critical platforms.

Deepexpertisein one or more areas: behavior planning and policy execution, imitation learning or reinforcement learning for real-world robot control, end-to-end learned autonomy systems, 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 in C++ and Python; experiencewith real-time autonomy stacks.

Demonstrated ability to take systems from researchprototypeto deployed productionplatform.

Track recordof driving architecture decisions acrossperception, planning, andcontrolsteams.

Preferred Qualifications

MS or PhD in Robotics, Computer Science, Machine Learning, or relatedfield.

Experience with autonomous vehicles, deployed robotics, or embodied AI systems in production.

Background in trajectory planning, behavior modeling, or autonomy policy design.

Familiarity with VLA architectures, foundation models for robot control, or large-scale pre-trained policies adapted for real-world deployment.

Experience building data flywheel or simulation-based training pipelines forproductionML systems.

Familiarity with functional safety standards, ISO26262or SOTIF.

Compensation & Benefits

Base Salary:$240,000 to $275,000

Equity:Stock options

Benefits:Medical, dental, vision, 401(k), paid time off

Location Requirement:Full-time, on-site at Sunnyvale HQ

Full-time