AI Robotics Research Engineer San Francisco, CA

Nimble; San Francisco (CA); Hybrid; USD 180,000 - 220,000; Full time

Benefits offered by this job

Unlimited Flexible Time Off

Health Insurance

Paid bonding time following a birth

Fully-paid parking spots

Referral Bonus

401k

Equity

Job summary

Nimble in San Francisco is seeking an AI Robotics Research Engineer to advance their robotics capabilities. You will design, develop, and implement advanced AI models, including robotic foundation models and reinforcement learning algorithms. The ideal candidate holds a Masters or Ph.D. in Robotics or Computer Science, has experience with deep learning models, and is skilled with real robotic hardware. Generous monthly salary of $180,000 - $220,000, with equity options and benefits including unlimited time off and health insurance.

Qualifications

• Experience training deep learning models for robotic manipulation or mobility.
• Experience working with real robotic hardware.
• Strong track record of publishing papers and/or deploying real-world applications.

Responsibilities

• Develop and train diffusion policies, VLMs, multi‑agent deep RL policies.
• Support implementation of models into production systems.
• Design data annotation and labeling.

Skills

Training deep learning models

Robotic manipulation experience

Simulation environments

Data collection pipelines

System architecture development

Education

Masters or Ph.D. in Robotics or Computer Science

Job description

Role Overview

Nimble is looking for an AI Robotics Research Engineer to help us advance our robotics moonshot by designing, developing, training, and implementing robotic foundation models, Vision‑Language‑Action Models, general‑purpose robotic AI models, and reinforcement learning algorithms controlling multi‑agent robot fleets.

You will play a critical role in working with our all‑star cross‑functional team to build models with immediate applications for the world’s biggest robotics opportunity.

Responsibilities

• Develop and train diffusion policies, VLMs, multi‑agent deep RL policies and more
• Develop data collection pipelines
• Design data annotation and labeling
• Support implementation of models into production systems

Qualifications

• Masters or Ph.D. in Robotics or Computer Science
• Experience training deep learning models for robotic manipulation or mobility
• Experience working with real robotic hardware
• Experience training models in simulation and developing simulation environments
• Experience collecting custom datasets
• Experience training on open‑source datasets
• Strong track record of publishing papers and/or deploying real‑world applications
• Experience with system architecture, design and development

Additional Requirements

• Must be able to work extended hours and weekends as needed
• Must be able to work in San Francisco

$180,000 - $220,000 a year

The above range is the salary range. This position will also receive generous equity for this position.

Benefits

• Unlimited Flexible Time Off – Enjoy the time you need to travel, rejuvenate, and connect with friends and family.
• Health Insurance – Nimble provides medical, dental, and vision insurance through several premier plans and options to support you and your family.
• Paid bonding time following a birth – Enjoy paid bonding time following a birth.
• Fully‑paid parking spots – Take the stress out of commuting with access to fully‑paid parking spots.
• Referral Bonus – Get a cash bonus for any friend or colleagues that you refer to us that we end up hiring.
• 401k – Contribute towards a 401k for retirement planning.
• Equity – Be an owner in Nimble through our equity program.

Nimble Robotics, Inc. is an equal opportunity employer. We make all employment decisions based solely on merit. We provide equal employment opportunity to all applicants and employees without discrimination on the basis of race, color, religion, national origin, ancestry, disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, sexual orientation, age, military or veteran status, or any other characteristic protected by applicable state, federal or local laws.