With this mission, we are looking for passionated machine learning engineers of
all levels who will develop robotics technology together with us to shape the new future of humanoid robots. You will work on a lean team without boundaries. Your influence will be on every single product that is shipped, without boundaries as well.
Job Responsibilities:- Develop and maintain machine learning models (e.g. VLM, VLA, RL, etc.) training and deployment pipelines that could scale to massive production.
- Work on efficient foundation models (e.g. small LLMs, weight sharing, model quantization, etc.) that can be deployed locally in humanoid robots.
- Work on efficient and effective ways to generate/leverage large scale dataset and computational resource.
- Explore novel ways to generate synthetic data to improve the data diversity & quality.
- Communicate and align with different teams on product needs across the company.
Minimum Qualification:- Strong python programming skills & software development, and strong experience with any major deep learning framework.
- Solid background in machine learning, natural language processing, computer vision, speech or data science.
- Open-minded, collaborative & humble personality.
Preferred Qualification:- Deep understanding of multimodal LLM modern architectures, "under the hood" LLM training knowledge, quantization techniques, etc.
- Record of publications, innovations or leadership.
What do we provide:- A fun, supportive and engaging environment
- Opportunities to make a significant impact on the future of transportation and robotics
- Opportunity to work on cutting edge technologies with the top talent in the field
- Competitive compensation package & benefits
- Snacks, lunches, and fun activities
The base salary range for this full-time position is $148,909 - $252,000, in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
