Remote opportunity at
JumioMachine Learning Engineer - IV (Computer Vision)
Jumio is seeking a remote Machine Learning Engineer IV specializing in computer vision to guide the creation and scaling of production-ready facial recognition systems. This position…
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About This Role
Jumio is seeking a remote Machine Learning Engineer IV specializing in computer vision to guide the creation and scaling of production-ready facial recognition systems. This position is intended for senior or staff level practitioners who bring extensive background in biometrics and computer vision, and who want to own machine learning systems end-to-end on AWS. The final classification for the job is established following completion of the interview process. Operating as…
Job Description
Jumio is seeking a remote Machine Learning Engineer IV specializing in computer vision to guide the creation and scaling of production-ready facial recognition systems. This position is intended for senior or staff level practitioners who bring extensive background in biometrics and computer vision, and who want to own machine learning systems end-to-end on AWS. The final classification for the job is established following completion of the interview process.
Operating as a business-to-business technology enterprise, Jumio focuses on eliminating financial crimes, money laundering, and digital identity fraud to secure the internet. The organization utilizes automation, artificial intelligence, machine learning, biometrics, and liveness detection to build verification tools utilized by global brands. Team members join a globally distributed workforce supporting diverse industrial sectors such as fintech, gaming, travel, financial services, and the sharing economy.
In this capacity, the engineer will direct the architecture of computer vision systems handling facial attributes, detection, recognition, and quality. Responsibilities include conducting fairness analyses, optimizing models for low-latency inference, and designing automated data pipelines using Airflow. The ideal professional demonstrates advanced Python proficiency, cloud experience with AWS, and the ability to mentor peers while championing technical standards across the computer vision group.
Responsibilities
- Lead architecture and creation of computer vision systems for biometrics covering face detection, attributes, recognition, and quality
- Conduct thorough fairness evaluations and benchmarks of biometric models across various operating scenarios and datasets
- Build, train, and refine models utilizing PyTorch, JAX, and/or TensorFlow
- Manage and evolve complete machine learning pipelines spanning data ingestion to deployment
- Construct automated pipelines via Airflow for data cleanup and ingestion
- Curate balanced training collections and create synthetic data to bridge diversity and quality gaps
- Drive production readiness by optimizing models for low-latency inference through distillation, quantization, TensorRT, or ONNX
- Supervise AWS deployments, mentor engineering colleagues, perform code and design checks, and promote best practices
Requirements
- Industry background in machine learning focused specifically on face analysis or biometrics
- Expertise in computer vision and biometrics with a strong emphasis on face recognition
- Practical experience measuring and mitigating algorithmic bias and disparate impact
- Advanced proficiency in Python alongside machine learning and vision packages such as OpenCV, Pillow, and PyTorch
- Ability to design end-to-end machine learning workflows utilizing orchestrators like Airflow
- Hands-on practice scaling training jobs across multi-GPU clusters and deploying services on AWS including EKS, EC2, and SageMaker
Qualifications
- Academic research publications in CVPR, ICCV, ECCV, or FG concerning face recognition, fairness, or image quality evaluation
- Background in large-scale search utilizing approximate nearest neighbor search algorithms and vector databases like Faiss or Milvus
- Familiarity with compliance, security, and privacy considerations in biometric architectures
- Edge or mobile device porting expertise using frameworks such as TFLite, LiteRT, or CoreML
- Practice utilizing diffusion models or GANs to produce synthetic faces for training purposes
Core Skills
Frequently Asked Questions
Answers are based only on the employer’s listing; where it doesn’t say, neither do we.
What is the remote work policy for this position?
The position is fully remote, with the headquarters listed in India.
What is the employment type?
The source posting does not specify whether the employment type is full-time or part-time, though it lists the role as Machine Learning Engineer IV.
What salary does this role offer?
The posting does not state a salary for this role.
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