5 hours ago
San Mateo, CA, USAIntern
H1B sponsor
Responsibilities
- Train reinforcement-learning policies for navigation, obstacle avoidance, and dynamic goal-seeking in complex 3D environments.
- Fuse learned cost shaping and value functions with trajectory optimization for safe, agile flight.
- Build scalable simulation datasets and training loops using domain randomization, residual learning, and safety filters.
- Develop human-in-the-loop shared-control policies that blend pilot intent, autonomy priors, and uncertainty-aware behavior.
- Explore decentralized multi-agent coordination for coverage, pursuit, and collaborative mapping.
- Prototype in simulation and validate policies through weekly flight tests on production-ready drones and edge compute.
- Collaborate with perception, mapping, controls, and product teams to transition research into field operations.
Requirements
- Be a PhD student in Robotics, Machine Learning, Controls, or a related field.
- Have strong fundamentals in reinforcement learning, control theory, and motion planning, with familiarity with safety and robustness concepts.
- Be proficient in Python and PyTorch, JAX, or Ray RLlib, and in at least one of C++ or CUDA.
- Have hands-on experience with robotics simulation using Isaac Lab, MuJoCo, or PyBullet and with sim-to-real techniques.
- Have experience training or deploying policies for navigation, manipulation, or locomotion on real robots or autonomous vehicles.
- Publications in venues such as CoRL, ICRA, IROS, RSS, or NeurIPS are desirable.
- Experience with onboard inference optimization, TensorRT, quantization, sparsity, diffusion policies, imitation learning/behavioral cloning, offline reinforcement learning, model-based reinforcement learning, multi-agent reinforcement learning, or distributed training is desirable.
Benefits
- Hourly compensation is $47/hr for undergraduates, $53/hr for master's students, and $70/hr for PhD students.
- Full-time employees are eligible to enroll in benefit plans and access various incentives and stipends.
Categories
ML EngineeringRobotics
About Skydio
Skydio builds autonomous drones, docking systems, and fleet management software for enterprise, public safety, and defense customers. It sells hardware with AI-based autonomy plus SaaS for fleet operations, inspections, and Drone-as-First-Responder programs. Founded in 2014 and headquartered in San Mateo, California, the company designs and assembles its products in the U.S., with manufacturing in Hayward, and its systems are used across utilities, law enforcement, and the U.S. military.