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. 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.
• Strong communication skills.

Role Purpose

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. 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.
Strong communication skills.

Role Purpose 

The Machine Learning Engineer III will play a critical role in advancing Jumio's Extraction team's mission to develop and enhance state-of-the-art solutions for data extraction for ID verification purposes. This role is essential for ensuring the highest standards of security and user verification through the application of advanced machine learning and deep learning techniques, ultimately contributing to Jumio's leadership in the online identity verification, eKYC, and AML solutions market

Role Value 

As a Machine Learning Engineer III at Jumio, you will have the opportunity to significantly impact the security and user experience of our ID verification solutions. Your expertise in machine learning, deep learning, and computer vision will drive the development of innovative algorithms that keep Jumio at the forefront of the industry. By deploying and maintaining these models in production, you will ensure the robustness and reliability of our solutions, supporting our clients across diverse industries such as Financial Services, Travel, Sharing Economy, Fintech, and Gaming. Your contributions will be pivotal in maintaining Jumio's reputation as the leading provider of online identity verification solutions, helping to meet the growing demand for secure and seamless user verification globally.

Example Responsibilities

. 

• Design and implement machine learning, deep learning, classical CV and NLP algorithms focused on data extraction.
• Research to support the deployment of advanced algorithms.
• Develop, evolve, and support production-quality code.
• Deploy models as AWS SageMaker endpoints or directly onto devices.
• Stay updated with the latest advancements in deep learning, computer vision, and NLP by engaging with academic papers and attending industry conferences.
• Work collaboratively with other engineers and product managers in an Agile development environment.

Experience and Qualifications 

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
• A minimum of 6+ years of commercial experience in the field of computer vision, ML or a related area, not including time spent studying (5 years with Master’s).
• Proficiency in computer vision, deep learning and natural language processing techniques.
• Proficiency in working with LLMs and VLMs.
• Hands-on experience with PyTorch or TensorFlow, OpenCV, SKLearn, and in developing production-grade Python code.
• Demonstrated experience in implementing best practices for monitoring and maintaining ML models in production environments.
• Experience in building, training, and deploying ML models to production environments.
• Strong communication and problem-solving skills.

Great to have Experience and Qualifications 

• PhD in Computer Science or related field with a specialization in computer vision, deep learning or NLP.
• Experience in developing algorithms for OCR, text extraction and text understanding.
• End to end experience (training, deploying, monitoring) with shipping VLM and LLM models in a production environment.
• Understanding of Spring / Java based system architectures.
• Experience with cloud environments - AWS / GCP.

Jumio Values 

• IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation

@Work
Our newest office, Jumio is in Prestige Tech Park III and growing fast. A hub of technical excellence with Machine Learning enablement at its core the engineers and team are committed to learning and innovation. They set the bar high. In a recent culture survey, these attributes were rated particularly highly in Jumio’s Indian offices.

Role Purpose: The Machine Learning Engineer IV will play a critical role in advancing Jumio's Fraud team's mission to develop and enhance state-of-the-art solutions for fraud detection for ID verification purposes. This role is essential for ensuring the highest standards of security and user verification through the application of advanced machine learning and deep learning techniques, ultimately contributing to Jumio's leadership in the online identity verification, eKYC, and AML solutions market

Role Value: As a Machine Learning Engineer IV at Jumio, you will have the opportunity to significantly impact the security and user experience of our ID verification solutions. Your expertise in deep learning and computer vision will drive the development of innovative algorithms that keep Jumio at the forefront of the industry. By deploying and maintaining these models in production, you will ensure the robustness and reliability of our solutions, supporting our clients across diverse industries such as Financial Services, Travel, Sharing Economy, Fintech, and Gaming. Your contributions will be pivotal in maintaining Jumio's reputation as the leading provider of online identity verification solutions, helping to meet the growing demand for secure and seamless user verification globally.

Example Responsibilities

. 

• Develop, maintain, and own key fraudulent CV models of Jumio, which shapes the whole fraud product offering of Jumio. 
• Design and implement machine learning, deep learning, classical CV focused on fraud detection.
• Research to support the deployment of the advanced algorithms.
• Deploy models as AWS SageMaker endpoints or directly onto devices.
• Stay updated with the latest advancements in machine learning, deep learning, and computer vision by engaging with academic papers and attending industry conferences.
• Work collaboratively with other engineers and product managers in an Agile development environment.

Experience and Qualifications 

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
• A minimum of 6+ years of commercial experience in the field of machine learning/deep learning, not including time spent studying (2 years with Master’s).
• Must have: experience with training of DL models for deepfakes, synthetic data, or gen AI data detection.
• Deep understanding of how to convert ML metrics to product goals. 
• Hands-on experience with PyTorch or TensorFlow, SKLearn, and in developing production-grade Python code.
• Demonstrated experience in implementing best practices for monitoring and maintaining ML models in production environments.
• Strong communication and problem-solving skills.

Great to have Experience and Qualifications 

• Experience in working with LLM’s or VLM’s.
• Work with image or video generation.
• Experience with cloud environments - AWS / GCP.
• Experience in working in global organizations across several timezones