Senior Machine Learning Engineer - (Biometrics)

Machine Learning Engineer – Biometrics (Computer Vision)
We’re looking for a Staff/Senior 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. Curate balanced training sets and generate synthetic data to address 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 and 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: Understanding of sources of algorithmic bias in Computer Vision and practical experience measuring and mitigating disparate impact
Strong Engineering: Expert proficiency in Python (including machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). Production‑ready, clean, modular code delivery
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
Strong communication skills
Equal OpportunitiesJumio is a collaboration of people with different ideas, strengths, interests and cultures. We welcome applications and colleagues from all backgrounds and all statuses. We are an Equal Opportunity Employer in accordance with federal, state, and local law.
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