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Gritt Robotics Inc
South San Francisco, California, United States
Source: Gritt Robotics Inc careers · View original posting
From Gritt Robotics Inc's posting. “We” and “our” refer to the employer.
Gritt is an intelligent system that combines robotics and AI to build the infrastructure that pulls society forward. Gritt deploys via simple attachments to common equipment found on construction sites and autonomously performs labor-intensive tasks, verification, and planning. Gritt systems are already building critical infrastructure in the harshest outdoor environments, starting with large-scale solar. The founding team includes experts in robotics and AI from Carnegie Mellon, Stanford, and MIT.
Gritt is backed by Obvious Ventures, Union Square Ventures, First Round Capital, Climactic, Congruent Ventures, and other leading firms.
Role: Robotics Software - Planning & Controls
Location: SF Bay Area (in-person)
We’re looking for an experienced Planning & Controls Engineer to join our team. As an early member, you will play a pivotal role in building and shaping the AI capabilities of our robots. You will work on challenging planning/control problems around manipulation and navigation in dynamic outdoor environments. You'll need to thrive in a fast-paced startup environment where you'll wear multiple hats and have a direct impact on our product's evolution.
Ideally, you have a proven track record of developing and deploying planning/control systems in production, and you're passionate about pushing the boundaries of what's possible in robotics with AI.
Develop and deploy state-of-the-art planning and control techniques for challenging manipulation and navigation problems.
Help drive our technical approach, with particular focus on real-world deployments.
Research and develop techniques around generating real-time, safe, efficient trajectories for multiple embodiments like robot manipulators and mobile robots.
Develop scalable planning representations for classical and learned techniques.
Leverage GPUs to generate and evaluate trajectories at scale.
Enable real-time, closed-loop control leveraging classical algorithms and ML.
Develop simulation techniques and metrics to benchmark and evaluate performance.
Collaborate with other teams in the company.
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