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Senior Machine Learning Engineer (Biometrics & Face Recognition)

ScanditTampereEngineering
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Salary
Not listed
Job type
Full-time
Experience
Senior · 5+ yrs
Posted
8 Oct 2026
Status
Open · checked 7d ago

About this role

Scandit is seeking a Senior Machine Learning Engineer in Tampere to build face recognition and identity verification technology for mobile devices. This role suits an experienced machine learning professional with a background in biometrics who wants to deliver on-device models for global users.

Role Overview

The Senior Machine Learning Engineer joins the ID Capture team at Scandit to develop the intelligence behind high-assurance identity verification. The position focuses on face recognition, face matching, liveness detection, and presentation attack detection that runs directly on mobile devices without cloud processing.

Key Responsibilities

Design, train, and evaluate models for face detection, face recognition, and 1:1 face matching against ID document portraits
Support initiatives regarding liveness and presentation attack detection to defend against spoofs, replays, and deepfakes
Establish quality metrics, test sets, and benchmarks that satisfy high-assurance and regulatory standards
Manage the complete model lifecycle encompassing data collection strategies, prototyping, training, debugging, and integration
Collaborate with C++ engineers to optimize models for mobile inference using quantisation, pruning, and mobile runtimes
Monitor developments in biometrics and face anti-spoofing research to guide product direction
Provide mentorship to engineers regarding machine learning methodologies

Requirements

Minimum of five years of professional experience as a machine learning engineer with production models delivered to real users
Practical experience working with biometrics including face recognition, face verification, liveness, or presentation attack detection
Proficiency in Python alongside experience with at least one deep learning framework, with PyTorch preferred
Deep understanding of security-sensitive system evaluation metrics such as FAR, FRR, demographic bias and fairness, and adversarial robustness
Strong communication skills with the ability to collaborate across multiple disciplines
Legal eligibility to work in the hiring location of Tampere

Nice to Have

Familiarity with standards such as ISO/IEC 30107, NIST FRTE, NIST FATE, or iBeta testing
Background in deploying machine learning models on mobile or edge devices using TFLite, ONNX Runtime, or Core ML
Working knowledge of C++

Skills and Tools

Python
PyTorch
ONNX
C++ on-device SDK
iOS and Android

Salary and Benefits

Flexible working arrangements with options for office, hybrid, or home-based schedules
Individual equity plan in a growth-stage company
Birthday leave
Company celebrations, global team outings, and hackathons
Office infrastructure designed for hybrid work in Tampere, Zurich, Warsaw, and London
Remote work support across Finland, Switzerland, Poland, the United Kingdom, Italy, and Germany

About the Company

Scandit provides technology that automates workflows and supplies actionable insights to businesses across multiple industries. Certified as a great place to work in seven countries, the organization maintains an inclusive environment that welcomes diverse backgrounds and experiences.

How to Apply

Interested candidates should apply directly on the official Scandit careers page.

Skills and tech stack

PythonPyTorchONNXC++iOSAndroidTFLiteCore MLDeep LearningMachine Learning

Questions candidates ask

Where is this job located?

This position is based in Tampere, with remote work support available in Finland, Switzerland, Poland, the United Kingdom, Italy, and Germany, alongside hybrid and office options.

What is the primary focus of the role?

The role centers on building machine learning architecture for identity verification, specifically focusing on face recognition, face matching, liveness, and presentation attack detection.

Do the models run in the cloud?

No, models run fully on-device on existing user phones without requiring cloud round-trips.

How many years of experience are required?

Candidates must have at least 5 years of experience as a machine learning engineer with production models deployed to real users.

What technical stack is used?

The tech stack includes Python, PyTorch, ONNX, C++ on-device SDKs, iOS, and Android.

Ready to apply?

The application is on the official Scandit careers page.

Apply on company site