Dexcom
Senior Algorithm Engineer - Sensing Algorithms
Remote California · Senior
Sponsorship not specified$111k-$185kDetected 1 day ago
PythonC++CMATLABAlgorithmsMachine LearningData AnalysisStatisticsRecruitingIntellectual PropertyElectrical EngineeringSignal ProcessingMedical DevicesResearchAnimal StudiesCommunicationCollaboration
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odds of building a lasting career here
54Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role78
Entry-level history0
PERM / green-card track0
Lottery odds (Level III)83
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~45% per draw at Level III). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
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About the role
- The Company Dexcom Corporation (NASDAQ DXCM) is a pioneer and global leader in continuous glucose monitoring (CGM).
- Dexcom began as a small company with a big dream: To forever change how diabetes is managed.
- That means personalized, actionable insights aimed at solving important health challenges.
Requirements
- Typically requires a Bachelor's degree in a technical discipline, and a minimum of 5-8 years related experience or Master's degree and 2-5 years equivalent industry experience or a PhD and 0-2 years experience.
- Travel Required:
Nice to have
- Experience with biosensors, physiological sensing, wearable systems, or analytical instrumentation.
- Experience with calibration, estimation, filtering, or measurement system algorithms.
- Experience transitioning algorithms from research into commercial products.
- Experience applying strong software engineering practices in data-driven application development.
- Publication, patent, or demonstrated record of innovation.
- A front row seat to life changing CGM technology.
- Learn about our brave #dexcomwarriors community.
- Growth opportunities on a global scale.
Compensation
- $111,100.00 - $185,100.00
Benefits
- A full and comprehensive benefits program.
- Access to career development through in-house learning programs and/or qualified tuition reimbursement.
- Education and Experience:
- Remote Workplace: Your location will be a home office; you are not required to live within commuting distance of your assigned Dexcom site (typically 75 miles/120km).
Company info
- Lead development of advanced algorithms supporting next-generation glucose sensing technologies.
- Develop physics-based, mechanistic, and data-driven models to characterize sensor behavior and improve measurement performance.
- Design and implement signal processing, estimation, calibration, detection, and predictive algorithms.
- Apply statistical modeling, machine learning, and data analytics techniques to extract insights from bench, preclinical, clinical, and real-world datasets.
- Drive clinical performance assessments and algorithm maturation in collaboration with sensor, systems, hardware, firmware, clinical, and product teams.
- Evaluate algorithm performance through simulation, modeling, and experimental analysis.
- Provide technical insights on algorithm architecture, design tradeoffs, verification strategies, and implementation approaches.
- Identify opportunities to optimize overall system performance and resource utilization.
- Facilitate algorithm design transfer activities with firmware, verification, and validation teams.
- PhD in Biomedical Engineering, Electrical Engineering, Applied Mathematics, Physics, Computer Science, Biophysics, Statistics, or a related field with 2 years of industry experience; or a Master's degree in a related field with 2-5 years of relevant experience.
- Expert-level proficiency in Python, MATLAB, C/C++, or similar technical computing environments.
- Deep expertise in statistical estimation, signal processing, optimization, and mathematical modeling.
- Strong understanding of machine learning techniques and practical model development.
- Demonstrated experience developing algorithms for sensing technologies, measurement systems, medical devices, or related disciplines.
This listing is sourced directly from Dexcom's careers page and normalized into a canonical job model.