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Senior Machine Learning Engineer

Tools for HumanityMunichEngineering
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Salary
Not listed
Job type
Full-time
Posted
21 Jul 2026
Status
Open · checked 8d ago

About this role

This role is for a Senior Machine Learning Engineer based in Munich, Germany, focusing on building and scaling computer vision and biometric systems for the World Network. This position suits an experienced engineer who wants to own end-to-end machine learning projects, from initial research and dataset curation to production deployment and monitoring within a fast-paced environment.

Role Overview

The AI & Biometrics team at Tools for Humanity is responsible for the machine learning infrastructure that powers the World Network, ensuring privacy-preserving proof of personhood at a global scale. As a Senior Machine Learning Engineer, you will drive applied computer vision research, improve biometric identification and anti-spoofing pipelines, and tackle complex real-world conditions like variable lighting, camera variations, and strict on-device resource limits. You will work alongside specialized subteams including Mobile, MLOps, and Face and Iris engineering to bring reliable AI systems into production.

Key Responsibilities

Own face machine learning projects completely from initial definition through data preparation, experimentation, validation, and post-launch monitoring.
Improve core biometric identification and anti-spoofing models by iterating on deep learning architectures, loss functions, and data pipelines within strict latency and memory limits.
Apply classical computer vision and image processing techniques when they provide more efficient or reliable solutions than deep learning.
Lead independent applied machine learning initiatives by forming written hypotheses, running ablations, and managing deployments effectively.
Inspect difficult image samples, drive data collection and labeling improvements, and address failure modes head-on.
Build robust evaluation pipelines and production monitoring to catch model regressions, track data drift, and identify new attack patterns.
Read and adapt relevant computer vision and biometrics research to improve existing systems.
Write clear design documents, technical proposals, and experiment reports that help team members build upon your work.
Shape technical standards across the AI & Biometrics team regarding evaluation methodology, model versioning, and experimentation discipline.

Requirements

Significant hands-on experience training, evaluating, and shipping deep learning systems for computer vision while managing strict latency and memory constraints.
Demonstrated ability to transform an ambiguous machine learning problem into a structured, actionable technical plan.
Strong practical knowledge of model training, encompassing data pipelines, augmentations, architecture selection, loss functions, optimization, and failure analysis.
Solid foundations in classical computer vision and image processing using tools such as OpenCV and NumPy.
Fluent in Python and experienced with a modern deep learning framework like PyTorch.
Experience designing evaluations that drive production decisions, including metric selection, calibration, dataset slicing, and regression analysis.
Ability to write maintainable, high-quality code for research and production environments.
A pragmatic, applied research mindset focused on knowing when to ship versus when to continue optimizing.
Strong written communication skills to clearly outline problems, requirements, and conclusions.
A collaborative and proactive operating style with the ability to take full ownership of projects.

Nice to Have

Direct experience with biometric verification, metric learning losses, presentation attack detection, or adversarial evaluation of machine learning systems.
Experience with edge optimization and on-device deployment including quantization, pruning, distillation, or deployment to mobile NPUs and embedded GPUs.
Hands-on experience with Rust for writing high-performance code paths.
Background in sensors, imaging, computational photography, or camera ISPs.
Familiarity with privacy-preserving computation or machine learning systems that interact with secure multi-party computation.

Skills and Tools

Python
PyTorch
Rust
Computer Vision
MLOps
OpenCV
NumPy

About the Company

Tools for Humanity designs and builds technology behind World, a real human network designed to help people navigate the age of AI. The tech stack includes the Orb for verification, World ID for private proof, and World App for digital identity management. Founded in 2019, the company brings together over 400 professionals across diverse technological disciplines with teams drawing experience from leading tech and research organizations. Backed by prominent venture capital firms and investors, the company has received extensive recognition across major publications for its innovative work in digital identity and cryptography.

How to Apply

Candidates interested in this position should visit the official company careers page to submit an application.

Skills and tech stack

PythonPyTorchRustComputer VisionMLOps

Questions candidates ask

Where is this job located?

This position is located in Munich, Germany, and is an on-site role.

What programming languages and frameworks are required?

The role requires fluency in Python and experience with modern deep learning frameworks such as PyTorch. Experience with Rust is listed as a nice-to-have skill.

What does the AI & Biometrics team do at Tools for Humanity?

The team owns the machine learning systems behind the World Network, including iris and face recognition systems, anti-spoofing pipelines, and models running on devices to make proof of personhood function at scale.

What level of experience is required for this role?

The position is a Senior Machine Learning Engineer role requiring significant hands-on experience training, evaluating, and shipping deep learning systems for computer vision.

How should I apply for this position?

You should apply directly on the official company careers page.

Ready to apply?

The application is on the official Tools for Humanity careers page.

Apply on company site