Terranova
AI

Controls Machine Learning Engineer

Terranova · Berkeley, CA

Actively hiring Posted 7 months ago

Company Description

Backed by leading climate and American dynamism investors, Terranova builds intelligent robotic systems to terraform the Earth itself - lifting land, restoring wetlands, and protecting critical infrastructure from floods and sea-level rise.

Our mission is to preserve the built environment, create new habitats, and usher in an era of abundance. Our work supports climate resilience, disaster recovery, and defense across the United States and beyond.

We’re assembling a world-class team that wants to work on something real, physical, and civilization-scale. If you want your work to reshape the world (literally), this is the place to do it.

Overview

We’re seeking a controls and ML specialist to develop algorithms that give our robotic systems adaptive, intelligent behavior. You’ll design and tune controllers, build dynamic models, and integrate them with perception and sensor data. This is a chance to bridge classical control with modern machine learning to shape how machines move through the Earth.

What You’ll Do

  • Develop and tune controllers (PID, MPC, optimal/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 (supervised or RL).
  • Integrate algorithms with firmware and cloud teams, ensuring real-time safety and stability.
  • Profile, optimize, and verify performance under latency, jitter, and compute constraints.

Useful Stack Familiarity

Python/C++ with PyTorch/JAX, MPC/OSQP/CasADi, EKF/UKF/factor graphs, system ID, RL (PPO/SAC) with safety shields, ROS2, ONNX/TensorRT, latency and jitter profiling.

Tags & focus areas

Used for matching and alerts on DevFound
Fulltime Machine Learning Pytorch Ai
Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.