Machine Learning Engineer Austria (remote)

Jumio; Österreich; Remote; EUR 70.000 - 110.000; Vollzeit

Zusammenfassung

Jumio seeks a Machine Learning Engineer with deep expertise in computer vision and biometrics to lead face recognition systems in production. You will build and train models, and own ML systems end-to-end on AWS. The final job level will be determined after the interview.

You will design CV-based biometrics, ensure fairness across datasets, and optimize pipelines for low-latency inference. Collaboration with the CV team and mentoring of junior ML engineers are key aspects of the role.

Qualifikationen

• 5+ years of industry ML experience, with 3+ years in biometrics or face analysis.
• Strong Python skills and production-ready code in CV/ML stacks.
• Experience deploying ML models to AWS with scalable pipelines.

Aufgaben

• Lead design and scaling of computer vision biometrics systems (face attributes, detection, quality, recognition).
• Analyze fairness and benchmark biometric models across datasets and conditions.
• Architect, train, and optimize models with PyTorch, TensorFlow, or JAX.
• Own end-to-end ML pipelines from data ingestion to deployment; design automated data workflows.
• Drive production readiness: low-latency inference, quantization, TensorRT/ONNX on AWS.
• Mentor engineers, review code/design, and promote best practices.

Kenntnisse

Python

Computer vision

Biometrics / Face analysis

Pillow

OpenCV

PyTorch

TensorFlow

JAX

Multi-GPU training

Production code quality

Tools

Airflow

SageMaker

EC2

EKS

TensorRT

ONNX

Milvus

Faiss

Jobbeschreibung

We’re looking for a Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process.

What You’ll Do

• Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition)
• Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions.
• Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX
• Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps.
• Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS.
• Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team.

What We’re Looking For

• Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis.
• Deep expertise in computer vision and biometrics, especially face recognition.
• Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact.
• Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code.
• Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow.
• Cloud Native: Hands-on experience scaling training jobs on multi-GPU clusters and deploying services on AWS (SageMaker, EC2, EKS).

Nice to Have

• Research Publications: Papers in CVPR, ICCV, ECCV, or FG related to face recognition, image quality assessment, or fairness.
• Large Scale Search: Experience with vector databases (e.g., Milvus, Faiss) and approximate nearest neighbor (ANN) search algorithms.
• Familiarity with privacy, security, and compliance in biometric systems.
• Mobile/Edge Experience: Experience porting models to edge or mobile devices utilizing frameworks such as CoreML, LiteRT, and/or TFLite.
• Synthetic Data: Experience using GANs or diffusion models to generate synthetic faces for training.

Jumio is a collaboration of people with different ideas, strengths, interests and cultures. We welcome applications and colleagues from all backgrounds and of all statuses.

At Jumio, we value belonging and believe in fostering an environment where a diversity of perspectives can thrive. Your responses will help us to reduce bias and increase diversity and inclusion across the company.

About Jumio:

Jumio is a B2B technology company dedicated to eradicating online identity fraud, money laundering and other financial crimes to help make the internet safer. We leverage AI, biometrics, machine learning, liveness detection and automation to create solutions that are trusted by leading brands worldwide and respected by industry thought leaders.

Jumio is the leading provider of online identity verification, eKYC and AML solutions. With a global footprint, we’re expanding the team to meet strong client demand across a range of industries including Financial Services, Travel, Sharing Economy, Fintech, Gaming, and others.