Senior Machine Learning Engineer, Behavioral Biometrics

Job not on LinkedIn

🔥 1 minute ago

🇺🇸 United States – Remote

💵 $127k - $160k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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Anthology Inc

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

💰 Venture Round on 2023-01

Anthology delivers education and technology solutions so that students can reach their full potential and learning institutions thrive. Millions of students around the world are supported throughout their education journey via Anthology’s ecosystem of flagship SaaS solutions and supporting services, including the award-winning Blackboard® (LMS), Anthology® Student (SIS/ERP), and Anthology® Reach (CRM). Through the Power of Together, we are uniquely inspiring educators and institutions with innovation that is meaningful, simple and intelligent to help customers redefine what’s possible and create life-changing opportunities for people everywhere. www.anthology.com.

📋 Description

• 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

• 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