At WHOOP, we're on a mission to unlock human performance. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. This position is with the Signal Processing team at WHOOP.
As a Signal Processing Engineer, focused on Deep Learning, you will be part of a cross-functional team composed of Signal Processing, WHOOP Labs, Firmware, and Data Science. You will work on raw sensor data and the core, fundamental features at WHOOP. This role will be tasked with solving the incredibly difficult technical problem of obtaining physiological information from noisy sensor data and enhancing diagnostic tools and control methodologies.
RESPONSIBILITIES:
- Utilize expertise in signal processing and time-series analysis to analyze biosensor systems and optimize their performance.
- Design and implement deep-learning (DL) and machine-learning (ML) models to extract valuable insights from large repositories of time-series/biosensor data.
- Conduct experiments and perform rigorous testing of the models. Optimize and fine-tune the DL/ML models for deployment in production systems, considering factors such as computational resources and real-time constraints.
- Write clean, efficient, and maintainable code that is production ready.
- Stay up to date with the latest advancements in DL research and technologies.
- Monitor and ensure the proper functioning of algorithms across our diverse user population, addressing any issues related to data and data quality.
- Contribute to ongoing research efforts and explore new features to improve the overall performance of our products.
- Validate wearable technology in clinical settings, analyze biomedical data, and prepare comprehensive reports for cross-functional teams.
- Join us in pushing the boundaries of wearable technology and positively impacting people's lives!
QUALIFICATIONS:
- PhD or Master’s degree in electrical engineering, biomedical engineering, computer science engineering, statistics, or a related field.
- Solid understanding of ML principles, algorithms, and particularly DL techniques. At the Signal processing team, we like to be aware of the mathematics behind the algorithms we use.
- Knowledge of and experience with signal processing, time-series analysis, biosensor systems, and analyzing biomedical data
- Academic research experience in DL and ML with published articles or minimum of 2 years of industry experience with focus on DL/ML algorithms
- Proficient in Python, and familiar with ML/DL libraries like scikit-learn, Tensorflow, PyTorch, Keras, etc.
- Excellent communication skills, both written and oral, to effectively convey complex technical concepts to diverse teams.
- Demonstrated ability to think innovatively and adapt to changing requirements while consistently producing high-quality reports within tight deadlines.
- Experience with multiple DL architectures including CNNs, RNNs, transformers. Being conversant with state-of-the-art DL and meta learning techniques is a significant plus.
- Experience with cloud computing resources is a plus.
Join us in pushing the boundaries of wearable technology and positively impacting people's lives!
This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.
Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.
WHOOP is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility
