About the role#
Terranova is seeking an intern to develop algorithms that give robotic systems adaptive, intelligent behavior. You will design and tune controllers, build dynamic models, and integrate them with perception and sensor data. This role bridges classical control with modern machine learning to shape how machines move through the Earth.
What you'll do#
- Develop and tune controllers like PID, MPC, and optimal or robust control for dynamic, nonlinear systems.
- Build and validate physical models for simulation, hardware-in-the-loop testing, and autonomy.
- Train and deploy ML models for perception, planning, or adaptive control using supervised or reinforcement learning.
- Integrate algorithms with firmware and cloud teams to ensure real-time safety and stability.
- Profile, optimize, and verify performance under latency, jitter, and compute constraints.
- Work in the environment of an early-stage startup.
What you'll need#
- Working towards a bachelor degree or higher in Computer Science, Robotics, or a related field.
- U.S. permanent residency.
- Evidence of being a maker through hobby or personal projects.
- Experience with Python, C++, PyTorch, or JAX.
- Familiarity with ROS2, ONNX, TensorRT, and LiDAR integration.
- Knowledge of MPC, OSQP, CasADi, EKF, UKF, and factor graphs.
- Skills in system identification and reinforcement learning, such as PPO or SAC with safety shields.
- PCB and embedded systems design skills are a bonus.
Location & details#
- Location: Berkeley, California.
- Term: Winter 2027 (January to May).
- This is a full-time, paid, on-site internship.
About Terranova
Terranova operates in the robotics engineering sector. The company builds robots that inject wood slurry underground to lift properties out of flood zones. This process aims to protect infrastructure and wetlands without disturbing the surface. Based in Berkeley, California, the firm maintains a team of 11 to 50 employees.
How to get in at Terranova
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