$60,000 – $90,000EntryFull Time
Boston Dynamics is seeking a passionate and driven Robotics Software Intern to join the Spot Autonomy team. You'll take on a research-to-production project advised by our autonomy engineers that allows you to test your results on our fleet of in-house robots. Your work will focus on scaling data capabilities and prototyping next-generation features that enhance how Spot explores and understands its environment. This internship demands a passion for robotics, a strong problem-solving aptitude, and a desire to learn in a dynamic, collaborative environment.
Key Responsibilities:
ML-based Robot Navigation: Contribute to the research and development of modern robot autonomy approaches (and the necessary tooling), such as end-to-end navigation policies, or traditional SLAM + ML hybrid approaches.
Simulation Development: Build out simulation capabilities, including diverse environments and dynamic animations, to improve sim-to-real reliability.
Autonomy Prototyping: Develop and implement prototype features for next-gen autonomy, such as autonomous exploration.
Hardware Validation: Conduct thorough testing and debugging of designs using our in-house robot fleet in real-world environments.
We are looking for:
Actively pursuing a PhD or research-based Master’s degree in Robotics, Computer Science, or a related field.
Strong proficiency in C++ and/or Python.
Familiarity with navigation fundamentals (Path Planning, SLAM) and/or Reinforcement Learning and/or LLM/VLM/VLA models.
Experience with machine learning frameworks such as PyTorch or TensorFlow.
Nice to Have:
Experience with robotics simulation environments (e.g., Isaac Sim, MuJoCo, Gazebo).
Experience working directly with robot hardware.
Proven track record of implementing autonomous mapping or exploration algorithms.
We are interested in every qualified candidate who is eligible to work in the United States. However, we are not able to sponsor visas for this position.
The hourly pay range for this position is between $30-$45/ hour. Base pay will depend on multiple individualized factors including, but not limited to internal equity, job related knowledge, skills, education and experience. This range represents a good faith estimate of compensation at the time of posting.
