Research Engineer – Machine Learning & Robotics
Jumio is hiring a Research Engineer – Machine Learning & Robotics. Level rates it ; you can apply on Jumio.
Level's read on this job
- Level rates this role Builds AI ●●●●: the job is building AI systems.
- The posting mentions Replicate, PyTorch and TensorFlow among its tools and skills.
- Level classes it as a junior role.
- Jumio has 16 other open roles on Level.
AI in this role
Build and scale systems for data collection, model development, and robotics integration supporting machine learning workflows.
Role Purpose
Jumio is looking for a Research Engineer with a foundation in machine learning, robotics, and data infrastructure to help build and scale the systems used for data collection, model development, and product improvement.
This role sits at the intersection of robotics, computer vision, and applied machine learning. You will work hands-on with robotic systems, ROS/ROS2-based modules, mobile data collection workflows, and ML pipelines that support training, evaluation, and production model performance. This is a strong opportunity for a new graduate or early-career engineer who wants to build practical systems that directly improve real-world AI products.
Role Value
High-quality data and reliable model evaluation infrastructure are critical to improving Jumio’s machine learning and computer vision capabilities. This role helps ensure that data collected from robotic systems and mobile applications is usable, scalable, and connected to the broader model development lifecycle.
The Research Engineer will support both the robotics/data collection environment and the ML development workflow, helping the team move faster, improve model quality, and better understand model performance in production.
Example Responsibilities
- Build and integrate ROS/ROS2-based modules to support 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 through robotic manipulators and in-house iOS and Android applications.
- Mine, query, and analyze data from internal databases to create features, identify trends, and generate insights that improve 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 that can be maintained and extended by other engineers.
- Collaborate cross-functionally with machine learning, engineering, product, and research teams to improve data collection, model development, and system performance.
Required Experience
- 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, especially 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.
Jumio Values:
IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation
Equal Opportunities:
Jumio is a collaboration of people with different ideas, strengths, interests and cultures. We welcome applications and colleagues from all backgrounds and of all statuses.
About Jumio:
Jumio is a B2B technology company dedicated to eradicating online identity fraud, money laundering and other financial crimes to help make the internet safer. We leverage AI, biometrics, machine learning, liveness detection and automation to create solutions that are trusted by leading brands worldwide and respected by industry thought leaders.
Jumio is the leading provider of online identity verification, eKYC and AML solutions. With a global footprint, we’re expanding the team to meet strong client demand across a range of industries including Financial Services, Travel, Sharing Economy, Fintech, Gaming, and others.
Applicant Data Privacy
We will only use your personal information in connection with Jumio’s application, recruitment, and hiring processes, as described in Jumio’s Applicant Privacy Notice. If you have any questions or comments, please send an email to privacy@jumio.com.
How we rate this
Research Engineer – Machine Learning & Robotics at Jumio rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you decide that one model's output is better than another's for a given task?
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where robotics was part of your work. What did you do?
- Tell me about a project where data infrastructure was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI Evaluation, Computer vision, Machine learning, Robotics, and Data Infrastructure. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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