Evan Albright

Software Engineering & ML Leader

Building production systems across healthcare and applied AI. Exploring consequential problems to found or co-found a company; open to EIR and embedded technical-leadership roles.

hi@evanalbright.com 650-380-3798 linkedin.com/in/evanmalbright evanalbright.com San Francisco Bay Area

Education

2018–2020Master’s in Data Science, University of Massachusetts Amherst

2010–2014Bachelor’s in Computer Science, Carleton College

Experience

2026–Current

Venture Exploration & Embedded Technical Leadership at Independent

  • Researching payment integrity, case readiness, fragmented clinical and operational data, and where applied AI can improve high-stakes work without obscuring ownership or failure.
  • Advising and embedding with teams that need hands-on technical direction and production delivery.

2023–2026

Machine Learning Engineer at Meta

  • Built model-training, personalization, and failure-analysis systems for a neural-input wristband across gesture, handwriting, and language-model workflows.
  • Automated model release, reducing roughly two weeks of intensive engineering work to a few days of light supervision.

2021–2023

Principal Software Engineer at Zus Health

  • Led a 14-person engineering and product team from pre-Series A through growth-stage delivery.
  • Built patient matching, record reconciliation, terminology normalization, and search infrastructure unifying millions of records from thousands of healthcare sources.
  • Shipped a real-time Master Patient Index with a sub-500 ms 99th-percentile service-level objective.

2019–2021

Data Scientist & Machine Learning Engineer at Omada Health

  • Built model-development and deployment infrastructure for more than ten data scientists, enabling models to reach production in weeks.
  • Trained a weight-quality model that reduced classification errors from 3% to 0.3%, protecting revenue for the company’s primary service.

2016–2018

Member of Technical Staff at Salesforce Einstein AI

  • Built APIs for training and serving computer-vision and language models, and co-invented a patented system for generating augmented neural-network training datasets (US10346721B2).

2014–2016

Nuclear Science & Engineering, Computer Scientist at TerraPower

  • Built reactor lifecycle simulation software used to evaluate next-generation nuclear reactor designs with faster, reproducible iteration.