Senior Machine Learning Engineer, Behavioral Biometrics

Anthology Inc

. Build authorship verification models as an open-set verification problem .

Posted 10/9/2026full-timeRemote • United StatesSenior💰 $127,000 - $160,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and optimizing authorship verification models, with a strong focus on behavioral signal extraction and model evaluation. Proficient in advanced Python programming and familiar with machine learning frameworks and techniques relevant to biometric data analysis.

Highest-signal resume keywords

Advanced Python ProgrammingExperience with Scikit-LearnFluency in PyTorchResearch Experience in Data Collection and ModelingUnderstanding of Evaluation Setups

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Authorship Verification ModelsBehavioral Signal ExtractionModel Inference OptimizationGradient-Boosted TreesLightGBMXGBoostRandom ForestsSequence ModelsData ValidationTechnical Writing

Soft Skills

Clear Technical WritingCollaboration with Engineers

Tools & Technologies

Scikit-LearnPandasNumPyPyTorch

Industry Keywords

Biometric DataKeystroke TelemetrySession LeakageFalse Accept RatesFalse Reject RatesPrivacy RequirementsFairness Requirements

Tech Stack

Tools & technologies

NumpyPandasPythonPyTorchScikit-Learn

About the role

Key responsibilities & impact

Build authorship verification models as an open-set verification problem
Extract behavioral signals from keystroke telemetry, including timing distributions, digraph and trigraph latencies, pause and burst structure, editing and revision behavior, and effort over time
Optimize model inference for latency, memory, and CPU on student laptops, including quantization and runtime selection
Design subject-disjoint evaluation splits and identify session leakage
Report false accept and false reject rates and measure performance across keyboard layouts, device types, non-native typists, and writers with motor differences
Test resistance to replay and synthetic keystroke generation
Help determine privacy and fairness requirements for biometric data
Partner with data and software engineers to move models from research notebooks to product releases and remain involved after deployment

Requirements

What you’ll need

M.S. with 3+ years of related experience, or Ph.D. in Computer Science (or related field)
Direct research experience through graduate lab work, thesis research, or publications
Experience carrying a question from hypothesis through data collection, modeling, and validation
Advanced Python with fluency in scikit-learn, pandas, NumPy, and a deep learning framework such as PyTorch
Strong with gradient-boosted trees, including LightGBM, XGBoost, and random forests
Comfortable using sequence models when temporal structure justifies the cost
Understanding of leakage, distribution shift, small-sample effects, and evaluation setups that flatter the model
Clear technical writing
Fluency in written and spoken English