Algorithm Engineer
$145,000–$175,000 year
Remote · California, United States
Job Summary
Lead development of biomedical machine learning and deep learning algorithms from data curation through deployment in cloud and embedded environments. Own the end-to-end algorithm development lifecycle, collaborate with cross-functional teams to define sensor and algorithm specifications and performance targets, translate system concepts into functional prototypes with engineers across sensor, firmware, mechanical, and software domains, conduct advanced exploratory data analysis and visualization, design and execute clinical studies to collect robust data for training and feasibility demonstration, clinically validate algorithm performance using rigorous statistical methods, support cloud and embedded implementations, contribute to the patent portfolio and technical publications.
Required Qualifications
- Ph.D. in Computer Science, Electrical Engineering, Biomedical Engineering, or related field with emphasis on deep learning, or equivalent combination of education and relevant industry experience in medical/physiological/fitness applications
- 4+ years of experience applying deep learning and machine learning algorithms to real-world data science problems
- Strong hands-on expertise with deep learning architectures and ML techniques
- Experience with signal processing theory, signal acquisition, processing, and feature extraction from noisy data
- Solid grasp of advanced statistical techniques and concepts
- Experience designing studies to test hypotheses with appropriate statistical power
- Familiarity with physiological signals and human physiology knowledge
- Ability to operationalize AI-assisted workflows to accelerate development
- Experience with cloud platforms (e.g., AWS) and modern production deployment workflows
- Strong software engineering practices, testing frameworks, and reproducibility in regulated medical systems
- Salary includes range, benefits include medical, dental and 401K
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