Research Engineer, Neuromotor Interfaces

Key Skills

Aartificial intelligence, Deep Learning, Effective communication skills, Jupyter Notebook, Machine learning techniques, matplotlib, Pandas, SciPy, Signal processing

Job Description

Research Engineer, Neuromotor Interfaces Responsibilities

• Plan and execute cutting-edge applied research to advance neuromotor interface capabilities.
• Design experiments to collect neuromotor and interaction data and evaluate human and model performance.
• Design methods, tools and infrastructure to analyze and leverage rich multimodal data sets.
• Define short-term research goals, informed by practical engineering concerns.
• Collaborate with research scientists and research engineers to deploy models that leverage fundamental scientific knowledge into new technology and user experiences.
• Help transition and deliver our work from research into product.

Minimum Qualifications

• Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
• Research-oriented software engineering skills, including fluency in python and in libraries for scientific computing (e.g. SciPy ecosystem, Pandas)
• Masters degree in Computer Science, Computer Engineering, or relevant technical field.
• Proficiency with quantitative methods (mathematics, statistics) and experience learning new technical knowledge and skills rapidly.
• Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment.
• Exposure to architectural patterns of large scale software applications.
• Experience with interdisciplinary and/or cross-cultural collaboration.

Preferred Qualifications

• PhD in one of the following fields: deep learning, artificial intelligence, machine learning, computer science, robotics, computer vision, computational neuroscience, signal processing, or related fields.
• Autonomously set technical and research direction.
• Comfort with rapid prototyping and disciplined software development processes.
• Experience developing end-to-end ML pipelines, including: dataset preprocessing, model development and evaluation, and software integration.
• Experience in software engineering in industry.
• Experience bringing machine learning-based products from research to production.
• Experience with scientific communication tools (Jupyter, Matplotlib).
• Research and software engineer experience demonstrated via an internship, contributions to open source, work experience, or coding competition