Perception - Machine Learning R&D Scientist
Bright Machines
Software Engineering
San Francisco, CA, USA
Posted on Tuesday, March 12, 2024
ABOUT THE ROLE
As a Machine Learning R&D Scientist in the Robot Perception team at Bright Machines, you will be one of the key contributors to research new innovative algorithms up to a production software level that will launch industrial-strength advanced features for the Bright Robotic Cells.
We are seeking highly skilled, highly motivated scientists and engineers to join us. As member of the perception team, your primary job is to do research and develop cutting-edge solutions, technologies and algorithms in the field of computer vision and machine learning, solving the greatest challenges in the industrial automation domain. You will design, develop and deliver solutions using state-of-the-art algorithms, leveraging research from academia and industry. You will have opportunity to work with several other scientists, as well as university and attends conferences to meets others researchers. With your teammates. you will participate to brainstorming session where you will provide your expertise and contribute to publications and patents.
WHAT YOU WILL BE DOING
- Research, develop and prototype advanced software technologies in the domain of machine learning, anomaly detection , domain adaptation, contrastive learning, self supervised learning and continuous training
- Develop models for specific use-cases and work on model generalization.
- Maintain and improve the current machine learning pipeline
- Analyze and improve performance, accuracy, robustness of the solutions currently deployed
- Communicating with other scientists and with the company, brainstorming and contribute to publications and patents
WHAT WE WANT TO SEE
- Phd Computer Engineering, Computer Science or the equivalent in experience with evidence of exceptional ability.
- 1+ year of relevant experience
- Programming language experience with C/C++, and Python
- Experience with statistical analysis of data and mathematical modeling
- Experience with developing machine learning
- Publications at leading conferences such as CVPR, ECCV/ICCV, NeurIPS, ICLR, ICRA, IROS, SIGGRAPH
- Excellent communication