2026 Summer Intern –PhD – Foundations: Localization, RVA & Mapping

Motional • Pittsburgh, PA

1d • Hybrid

About The Position

The Actions Interns will focus on generating reliable, safe, and efficient actions for the system—translating perception and behavior decisions into executable motions or outputs. This role may involve action modeling, motion planning, control algorithms, trajectory optimization, reinforcement learning, generative models, data pipeline development, ML frameworks, or actuator-level experimentation, depending on team needs.

Requirements

• Currently pursuing a Masters/PhD degrees in Computer Science, Machine Learning, Robotics, or a related field
• Strong programming skills (Python required; C++ preferred)
• Coursework or project experience in one or more: Motion planning Control systems Trajectory optimization Robotics or autonomous systems Machine learning
• Familiarity with simulation tools

Nice To Haves

• Experience with classical control (PID, MPC) or modern learning-based control
• Knowledge of kinematics, dynamics, or robotics frameworks
• Understanding of actuator constraints, latencies, and real-time execution considerations
• Experience developing machine learning models for motion planning in a real-world robotic setting

Responsibilities

• Develop or refine action-generation algorithms and/or models, motion planners, and trajectories
• Run simulation or real-world experiments to evaluate action execution quality
• Support analysis and tuning of action performance (latency, smoothness, stability).
• Work with Behaviors to ensure action feasibility and alignment with higher-level goals
• Collaborate with Perception to evaluate downstream impacts of perception noise or drift
• Document tools, experiments, and action models clearly

What This Job Offers

• Career Level: Intern
• Education Level: Ph.D. or professional degree