Research Engineer
2 weeks ago
Meta Reality Labs is looking for a Research Engineer to help us unleash human potential by eliminating the bottlenecks between intent and action. To achieve this, we're building a practical neural interface drawing on the rich neuromotor signals that can be measured non-invasively using electromyography (EMG). Our research lies at the intersection of computational neuroscience, machine learning, signal processing, statistics, biophysics, motor learning, AR/VR and human-computer interaction. We're looking for people who want to shape the future of this technology and are excited about joining our collaborative research team. As a Research Engineer working at the Reality Labs, you will be responsible for the implementation and acceleration of our EMG machine learning platform; creating new AI models, tools, and infrastructure that unlock the capabilities of our technology; productionizing our research results, and working with scientists, software engineers, hardware engineers and designers to advance the company's AI-driven AR/VR agenda.
Research Engineer - Reality Labs Responsibilities
- Research and develop Deep Learning or other computational models with at least one of Computer Vision, Natural Language Processing, and EMG signal processing.
- Design methods, tools and infrastructure to analyze and leverage rich multimodal data sets.
- Collaborate with research scientists and research engineers to develop innovative deep learning models that define the next generation EMG-based AR/VR interaction techniques.
- Define short-term research goals, informed by practical engineering concerns.
- Help transition and deliver our work from research into product.
- Adapt standard machine learning and signal processing methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
- Masters degree in Computer Science, Computer Engineering, or relevant technical field.
- Experience with developing machine learning models at scale from inception to business impact.
- Research experience in machine learning, deep learning, computer vision and/or natural language processing.
- Programming experience in Python and hands-on experience with frameworks such as PyTorch.
- Exposure to architectural patterns of large scale software applications.
- Ph.D. degree and publications in machine learning, speech and language technologies, signal processing, electrical engineering, computer science, computational neuroscience, statistics, physics, or related fields.
- First-author publications at peer-reviewed AI or signal processing conferences (e.g. NeurIPS, CVPR, ICML, ICLR, ICCV, ACL, Interspeech and ICASSP).
- Comfort with rapid prototyping and disciplined software development processes.
- Experience with productizing new research results.
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