AuthenticID is solving the biggest business issue in the world today: Fraud.

Fraud losses are skyrocketing for companies because the old model of verifying identity (“something you know”) isn’t working with so many data breaches, hacks, dark web data sales and sophisticated fake ID creation.

AuthenticID uses a next-generation model of verifying identity based on combining a government-issued ID (“something you have”) with biometric data of face/voice/fingerprint (“something you are”). Our solution provides identity verification in seconds using a mobile phone and is able to defeat most fraud attempts using advanced AI capabilities.

With many new Fortune 500 clients, AuthenticID is going through a rapid growth phase and needs people who understand this type of scaling and bring a passion to help solve big problems that affect millions daily.

"Okay?" You might be asking. It's great to talk about the business of privacy, but... what exactly are these solutions you're building? …We can’t tell you quite yet.

Our job is to keep our work out of the wrong hands. But more than that, we need people on our team who believe in the mission to safeguard privacy amidst 21st century interactions. It’s more than a job, it’s a movement on the frontlines of privacy and commerce affecting tens of millions every year.


The Senior Computer Vision Reinforcement Learning Researcher reports to the Research Manager and will be a direct contributor to R&D’s transformative research initiatives. This role applies statistical rigor (in Python) to the flows of incoming data, classification model outputs, pre-output embeddings and feature distributions, building up metrics, semantic alerts, model fusion and more to produce intuitive sensitivity controls for AI product customization. This role also equips researchers with numerical tools to aid the algorithm development process and standardize acceptance criteria.

Top 3 key outcomes in the first year include:

1) Establish a Baseline – Organize and characterize distributions of key static datasets, live data flows and decisions generated with descriptive statistics.

2) Transform – Derive feature embeddings from heuristic code, convert categorical datasets into weight of evidence features, discover lower-dimensional projections to improve model training efficiencies. Feed into existing feature discovery/importance and AutoML frameworks, and expand capabilities of both.

3) Innovate – Apply and create fundamentally original solutions in reinforcement learning for computer vision tasks such as classification, segmentation, image retrieval, background removal and more.


● Track record of success in descriptive statistics and exploratory data analysis

● Extensive experience with proximal policy optimization research or engineering

● Structured data analysis, statistical classification, survival analysis

● Computer Vision and Image Processing experience

● Excellent visual and written communication skills

● AuthenticID company values and culture fit

Master’s or Ph.D. in statistics, mathematics or similar field of formal numerical analysis (theoretical physics, quantitative analysis, etc.)

● Background check and drug screen required


● Mathematics, Statistics, Information Theory

● Proficient in assorted flavors of multivariate ANOVA, as well as the analysis of non-normally distributed and heteroscedastic data

● Python: 3+ years, proficient with Pandas, statsmodels, scikit-learn

● C++/Julia (nice to have)

● Automated Feature Discovery: 1+ years Featuretools or similar

● AutoML: 1+ years MLJAR, AutoGluon or similar

● Neural Architecture Search: 1+ years ARCHAI, Compose or similar

● D3.js, seaborn, other visualization libraries

● Data: 3+ years SQLite/MySQL and MongoDB

● AWS EC2 and S3 (1+ years required), Sagemaker and Lambda (nice to have)


● Competitive salary and option grants

● Flexible hours and recovery days

● Medical & Dental Insurance, and Life

● Once-in-a-lifetime experience taking a startup into scale mode, working directly with experienced founders and a diverse, fun-loving and hardworking team

LOCATION: 100% remote in the United States or Seattle, WA