Machine Learning Engineer, EMEA

Jumio; United States; Remote; USD 170,000 - 250,000; Full time

Job summary

Jumio is seeking a senior machine learning engineer to lead biometric vision model development for face analysis and recognition, spanning data, fairness evaluation, and low-latency cloud inference.

You will design models, benchmark across datasets, mitigate bias, and own end-to-end ML pipelines, including data ingestion, training, and deployment, while mentoring engineers. Role level will be decided during interview.

Qualifications

• Multiple years of industry machine learning experience, including biometrics or face analysis.
• Deep computer vision expertise with face recognition.
• Experience identifying, measuring, and mitigating bias in CV.
• Expert Python skills with production-ready code.
• End-to-end ML pipelines and Airflow workflows.
• Experience scaling training on multi-GPU clusters and deploying on AWS.

Responsibilities

• Design biometric vision systems for face attributes, detection, and recognition.
• Benchmark models across datasets and operating conditions with fairness checks.
• Train and optimize models using PyTorch, TensorFlow, and/or JAX.
• Own data-to-deployment ML pipelines, including data ingestion and cleaning.
• Prepare models for production inference with quantization, distillation, TensorRT or ONNX, and manage cloud deployment.
• Mentor engineers and review code and designs across the team.

Skills

Python

Machine Learning

Computer Vision

Bias mitigation

Airflow

AWS

Multi-GPU training

Tools

PyTorch

TensorFlow

JAX

ONNX

TensorRT

Job description

Lead the development and production deployment of computer vision models for biometric applications, with a focus on face analysis and recognition. The work spans model design, training data, fairness evaluation, and low-latency inference on cloud infrastructure. The role level will be determined during the interview process.

Responsibilities

• Design biometric vision systems for face attributes, detection, image quality, and recognition.
• Benchmark models across datasets and operating conditions, and assess fairness and disparate impact.
• Train and optimize models with PyTorch, TensorFlow, and/or JAX.
• Own data-to-deployment ML pipelines, including ingestion and cleaning workflows, balanced training sets, and synthetic data generation.
• Prepare models for production inference using techniques such as quantization, distillation, TensorRT, or ONNX, and manage cloud deployment.
• Mentor engineers, review code and designs, and support technical practices across the team.

Requirements

• Multiple years of industry machine learning experience, including at least three years in biometrics or face analysis.
• Deep computer vision expertise, particularly in face recognition.
• Practical experience identifying, measuring, and mitigating algorithmic bias in computer vision.
• Expert Python skills, including machine learning and image processing libraries, with a record of production-ready code.
• Experience designing end-to-end ML pipelines and using workflow orchestration tools such as Airflow.
• Experience scaling training on multi-GPU clusters and deploying services on AWS.

Nice to have

• Research publications on face recognition, image quality, or fairness.
• Vector database and approximate nearest neighbor search experience.
• Familiarity with privacy, security, and compliance for biometric systems.
• Experience deploying models to mobile or edge devices, or generating synthetic faces with GANs or diffusion models.
• Strong communication skills.