Jumio is a B2B technology company dedicated to eradicating online identity fraud, money laundering, and other financial crimes, aiming to make the internet safer. They utilize AI, biometrics, machine learning, liveness detection, and automation to create trusted solutions for leading global brands. Jumio is a leading provider of online identity verification, eKYC, and AML solutions, with a global presence and expanding to meet client demand across various industries including Financial Services, Travel, Sharing Economy, Fintech, and Gaming.

About the Position

Introduction

Jumio is seeking a Research Engineer with a background in machine learning, robotics, and data infrastructure. This role focuses on building and scaling systems for data collection, model development, and product enhancement. This position is ideal for a new graduate or early-career engineer passionate about developing practical systems to improve real-world AI products.

Responsibilities

Build and integrate ROS/ROS2-based modules for robotic navigation, manipulation, and data collection workflows.
Replicate and integrate mobile and web UI environments into robotic testing and data collection systems.
Build, maintain, and improve training and test datasets collected via robotic manipulators and in-house iOS/Android applications.
Mine, query, and analyze data from internal databases to generate features, identify trends, and provide insights for product and model development.
Develop tools and processes to monitor data quality, model performance, and model accuracy in production environments.
Implement end-to-end machine learning workflows, including data preparation, model training, testing, evaluation, and deployment support.
Write clean, modular, well-documented C++ and Python code for maintainability and extensibility.
Collaborate cross-functionally with machine learning, engineering, product, and research teams to enhance data collection, model development, and system performance.

Requirements

Bachelor’s or Master’s degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field.
1–2 years of relevant industry, internship, or research experience in machine learning, robotics, computer vision, or related technical areas.
Hands-on experience with ROS and/or ROS2, including building or integrating modules for robot navigation, manipulation, simulation, or data collection.
Strong foundation in machine learning fundamentals, with experience implementing models in Python using frameworks such as PyTorch, TensorFlow, scikit-learn, or similar.
Experience working with databases, writing queries, and building or maintaining data pipelines for training, testing, or evaluation.
Strong programming skills in Python and C++, with an emphasis on clean, reliable, well-documented code.
Ability to work hands-on with physical hardware, debug system behavior, and translate research or prototype work into scalable engineering solutions.

Nice to Have

Experience with robotic manipulators, mobile robot platforms, or lab-based robotic systems.
Familiarity with iOS and/or Android development, particularly for hardware-integrated data collection applications.
Experience with data collection pipelines for computer vision, biometric systems, identity verification, or similar applied AI domains.
Exposure to production ML observability, model monitoring, drift detection, or data quality monitoring tools.
Familiarity with cloud platforms such as AWS, including S3, EC2, SageMaker, or similar tools for storage, compute, and model deployment.
Experience working in cross-functional environments with machine learning engineers, software engineers, researchers, and product teams.