Senior Software Engineer - Machine Learning

We are seeking a Machine Learning Engineer with strong production-level Python development skills to join our algorithm team. The role involves the full spectrum of machine learning development—from Exploratory Data Analysis, early-stage prototyping, and algorithm tuning. This engineer will need to hand-off their work product to firmware and software engineers and support these engineers in development and deployment of production software.

Key Responsibilities

• Conduct ETL, EDA, and feature engineering.
• Design, prototype, and implement machine learning algorithms and data analysis procedures, with emphasis on biomedical time-series data and small datasets.
• Develop robust, practical methods for classification, anomaly detection, regression, and prediction problems.
• Develop, test, and maintain production-grade python following best practices in version control, testing, and documentation.
• Collaborate across teams to translate algorithmic concepts into rigorously tested real-world embedded and/or cloud implementations.
• Communicate findings and methods clearly to both technical and non-technical stakeholders.

Qualifications

• Experience: Minimum of 5+ years designing, testing, and deploying machine learning algorithms in real-world applications.
• Education: B.S. or M.S. in Computer Science, Electrical Engineering, or a closely related field.
• Core foundations: Strong, first-principles understanding of probability, classical statistics, linear algebra, optimization, and classical as well as modern machine learning methods combined with keen intuition.

• Technical proficiency:

• Deep expertise in Python (including pandas, numpy, scipy, matplotlib/plotly, scikit-learn, and testing frameworks such as pytest or unittest).

• Experience with Matlab and C/C++ desired.

• High degree of comfort with CI platforms, Git, Jira, and Bitbucket.

• Knowledge of signal processing methods is desired.

• Code Development: Proven experience building and maintaining production-quality python-based architectures.

• Approach: Combines systematic, detail-oriented thinking with creativity and the ability to apply the 80/20 rule effectively when quick turnarounds are expected.

• Communication: Rock solid written and verbal communication skills for both technical and non-technical audiences.

9/80 Work Week