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Meta • New York, New York, United States
Role & seniority: Engineering Manager (senior management of research & engineering team)
Stack/tools: sensors/wearables hardware; signal processing; machine learning; biophysical signal simulation; SciPy-style scientific computing tools; cross-disciplinary hardware-software collaboration
Lead a team of research scientists/engineers to deliver high-quality products and solutions; provide career guidance and performance feedback
Collaborate with hardware, ML research, and engineering teams to build scalable systems characterizing sensor performance and its impact on features
Develop scalable methodologies/tools to simulate biophysical signals, improve ML models considering sensor limitations, and define engineering strategies to meet product targets
BS in CS, CE, or related field (or equivalent practical experience); work authorization
Experience with sensors/wearables in consumer hardware (e.g., biosensors, ECG/PPG, capacitive sensing, EMG)
Experience defining technical direction and mentoring contributors
MS/PhD in ML, AI, CS, EE, statistics, data science, signal processing, etc.
4+ years post-PhD in related R&D; strong quantitative methods
Research-oriented software engineering; proficiency with scientific computing libraries
Cross-functional collaboration experience; demonstrated people-management
Location & work type: not specified in the posting; assume full-time r
Meta is seeking an Engineering Manager with expertise in product-focused signal processing and sensor development to help us create novel wearable devices and algorithms that will become one of the main pillars for interaction with the virtual and augmented world. Help us unleash human potential by removing the bottlenecks between user intent and action.
Responsibilities
Lead a team of research scientists and research engineers to deliver high-quality products and solutions Manage career guidance for the team through regular feedback and tracking performance Collaborate with cross functional teams including hardware, machine learning research and engineering teams to develop scalable systems to characterize sensor performance and their impact on product features Develop scalable methodologies and tools to simulate biophysical signals and their approximations Explore methods to improve ML models for product features by incorporating knowledge of sensor performance limitations Develop and implement engineering strategies to achieve product development targets Foster a work environment of continuous learning, growth and improvement
Minimum Qualifications
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment Experience with sensors, wearables development in consumer hardware space (e.g. biosensors or novel input devices such as electrocardiography (EKG/ECG), photoplethysmography (PPG), capacitive sensing, electromyography, etc) Experience defining technical direction for a team and supporting the work of the team towards those goals Experience with mentoring individual technical contributors
Preferred Qualifications
MS/PhD in machine learning, AI, computer science, electrical engineering, statistics, applied mathematics, data science, signal processing, optimization or related technical fields 4+ years of experience after PhD in related industry R&D setting Proficiency with quantitative/statistical methods Research-oriented software engineering skills, including fluency with libraries for scientific computing (e.g. SciPy ecosystem) Experience collaborating with multiple interdisciplinary and/or cross functional teams Demonstrated experience in managing technical teams including performance management