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Senior Machine Learning Engineer

Tools for Humanity· Engineering
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MunichFull-timePosted 3mo ago

About the role

Senior ML Engineer within the AI & Biometrics team focused on face verification, anti-spoofing, and related biometric systems for the World Network. Own end-to-end ML projects, improve core models under strict latency/memory constraints, and collaborate across mobile, MLOps, and product teams.

Responsibilities

  • Own face machine learning projects from initial problem definition through data preparation, experimentation, evaluation, production validation, and monitoring, partnering with different teams.
  • Improve core biometric identification and anti-spoofing models, training and iterating on deep learning architectures, with model size, latency, and memory budgets as design constraints.
  • Use classical computer vision and image processing when appropriate (preprocessing, lightweight on-device components, or diagnostic tools).
  • Lead independent applied ML initiatives end-to-end: form hypotheses, design ablations, run experiments, interpret results, decide when to ship.
  • Work directly with face images and datasets: improve collection/labels, inspect samples, identify failure modes, drive model/evaluation changes.
  • Build evaluation pipelines to catch regressions, monitor data drift and new attack patterns, and improve internal tools for data analysis, training, evaluation, visualization, red-teaming, and monitoring.
  • Read/evaluate relevant CV/biometrics research and adapt ideas to our systems.
  • Write design documents, experiment reports, post-launch analyses, and technical proposals for reuse beyond the project.
  • Help shape technical standards across the AI & Biometrics team (evaluation methodology, experimentation discipline, model versioning, monitoring).

Qualifications

  • Significant hands-on experience training, evaluating, and shipping deep learning systems for computer vision with latency/memory constraints.
  • Experience turning ambiguous problems into structured technical plans.
  • Strong practical knowledge of data pipelines, augmentations, architecture selection, losses, optimization, hyperparameter tuning, and failure analysis.
  • Strong foundations in classical CV and image processing (OpenCV, NumPy), Python, and PyTorch.
  • Experience designing evaluations that support production decisions (metrics, thresholds, calibration, dataset construction, slicing, leakage prevention, regression analysis).
  • Ability to write maintainable research and production-grade code.
  • Pragmatic, applied-research mindset with clear decision-making on shipping vs further optimization.
  • Strong written communication and collaborative, independent working style.
  • Driver’s-seat operating style: ownership end-to-end and accountability for production decisions.

Skills

Required:Face machine learningClassical computer vision and image processingDeep learning frameworksModel evaluation and production readinessData pipelines / augmentation
Last updated Jul 22, 2026. Interested? Apply on the company site.
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About Tools for Humanity

Tools for Humanity is a technology company building for humans in the age of AI.

Tools for Humanity is a technology company building for humans in the age of AI.

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