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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in machine learning and biosignal processing, with a strong focus on developing and deploying advanced algorithms for wearable technology. Proven ability to translate complex physiological insights into actionable strategies while collaborating across multidisciplinary teams.
Highest-signal resume keywords
Machine Learning ExpertiseBiosignal ProcessingDeep Learning FrameworksCloud Systems FamiliarityConsumer Health Tech Experience
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningBiosignal ProcessingSensor FusionMultimodal Time-Series Data AnalysisAlgorithm DevelopmentModel Architecture DesignSignal ProcessingData AnalysisTransformersRNNs
Soft Skills
CollaborationCommunicationProblem-SolvingAutonomyLeadership
Tools & Technologies
PyTorchNumPySciPyPandasScikit-learnCloud DatasetsPrototypesHardware Evaluation KitsBenchtop Testing Setups
Certifications & Qualifications
Master’s DegreePhD
Industry Keywords
Wearable TechnologyDigital Health ApplicationsConsumer Health TechPhysiological MetricsAgile Environment
Tech Stack
Tools & technologiesCloudNumpyPandasPyTorchScikit-Learn
About the role
Key responsibilities & impact- Take full technical ownership of the algorithm lifecycle, from physiological background and signal processing to model architecture design, evaluation, and scaling for production.
- Develop and deploy state-of-the-art ML algorithms leveraging deep learning, including Transformers, RNNs, and probabilistic models, to extract physiological metrics across diverse user populations.
- Solve real-world challenges such as motion artifacts and environmental noise.
- Leverage Oura’s large-scale cloud datasets and work hands-on with prototypes, hardware evaluation kits, and benchtop testing setups.
- Translate complex algorithmic results and physiological insights into clear technical strategies and strategic narratives for senior leadership.
- Collaborate with hardware, firmware, software, and science teams to shape next-generation features and product roadmap.
Requirements
What you’ll need- 5–7+ years of hands-on experience in machine learning, biosignal processing, sensor fusion, and analyzing real-world, multimodal time-series data.
- Expertise with modern ML frameworks (PyTorch) alongside the scientific computing stack (NumPy, SciPy, pandas, scikit-learn).
- Strong domain knowledge of human physiological systems underlying wearable biosignals, paired with the engineering intuition needed to extract clean signals from noisy data.
- Familiarity with modern data infrastructure, scalable cloud systems, and a proven track record of moving ML models from experimental research into production software.
- Master’s or PhD in Computer Science, Machine Learning, Biomedical Engineering, Signal Processing, Applied Mathematics, Physics, or a closely related field (or equivalent practical track record).
- Comfortable working in an agile environment with high autonomy, taking complete ownership of algorithm development from early-stage concept testing to deployment.
- Direct experience in consumer health tech, wearable hardware or digital health applications.
- Prior experience working within cross-disciplinary teams spanning software engineering, hardware development, and clinical research.
Benefits
Comp & perks- Competitive salary
- Lunch benefit
- Wellness benefit
- Flexible working hours
- Collaborative, smart teammates
- An Ōura ring of your own
- Wellness Time Off