Research Scientist CTRL Labs
Job Summary
Reality Labs at Meta is seeking a Research Scientist to develop neuromotor interfaces using non-invasive surface electromyography (EMG). The role involves creating novel signal processing and machine learning models to translate human intent into digital action. You will work in a multi-disciplinary team to bridge the gap between advanced research and practical product applications.
Responsibilities
- Develop Deep Learning/computational models
- Design infrastructure for multimodal data analysis
- Lead technical direction for research projects
- Transition research outcomes into product features
- Optimize ML methods for parallel environments
Required Skills
- Ph.D. in CS, EE, or related field
- Python proficiency
- Experience with PyTorch
- Large-scale ML model development
- Signal processing research expertise
Job Details
Responsibilities:
- Research and develop Deep Learning or other computational models.
- Design methods, tools and infrastructure to analyze and leverage rich multimodal data sets.
- Set technical direction for a project of 2-3 researchers and engineers.
- Help transition and deliver our work from research into product.
- Adapt standard machine learning methods to best leverage modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
Minimum Qualifications:
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
- Ph.D. degree in Computer Science and Engineering, Electrical Engineering, Statistics/Mathematics.
- Experience with developing machine learning models at scale from inception to business impact.
- Programming experience in Python and hands-on experience with frameworks such as PyTorch.
- Exposure to architectural patterns of large scale software applications.
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.
Preferred Qualifications:
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at peer-reviewed AI conferences (e.g. NeurIPS, CVPR, ICML, ICLR, ICCV, ACL, and ICASSP).
- Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub).
- Experience bringing machine learning-based products from research to production.