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Whoop

Whoop - Senior Machine Learning Scientist (Sensor Intelligence)

Boston, MA$150k - $215k6d ago
In OfficeSeniorNACloud ComputingArtificial IntelligenceSenior Data ScientistMachine Learning EngineerAWSGCPMLOpsCoaching

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Requirements

• Bachelor's degree in Computer Science, Electrical/Computer Engineering, Applied Mathematics, or a related field; Master’s or PhD degree preferred • 5+ years of experience as a Machine Learning Scientist or similar role with a focus on applied research, preferably related to voice and/or text-based conversational systems • Experience training, fine-tuning, and deploying state-of-the-art deep learning architectures to production • Experience with time-series foundation models and self-supervised training approaches • Experience pre-training and fine-tuning small language models and/or building natural language understanding (NLU) models than run on resource-constrained targets • Experience with cloud platforms (AWS or GCP) and familiarity with modern MLOps practices such as CI/CD, model versioning, monitoring, and observability • Strong communication and collaboration skills across cross-functional teams • Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions • 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.

Responsibilities

• Research, architect, and develop ML systems for member coaching distributed between edge hardware and the cloud • Collaborate with machine learning and edge ML engineers to translate prototypes into production • Partner with product and user experience teams to ensure consistent user experience in bandwidth-constrained environments and to align with member impact and health insights goals • Contribute to architectural decisions and mentor team members in ML best practices

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