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Internship Machine Learning Startup Jobs in Kansas

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... Previous software engineering experience via an internship, work experience, or coding competition

New

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... Previous software engineering experience via an internship, work experience, or coding competition

New

Our data products - derived from satellite imagery and machine learning - give utilities a clearer ... Prior work in a high-growth startup or mission-driven company

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Internship Machine Learning Startup information

What is the difference between Internship Machine Learning Startup vs Data Science Intern?

AspectInternship Machine Learning StartupData Science Intern
Required CredentialsBasic programming, statistics, coursework in MLSimilar; often includes coursework in data analysis and statistics
Work EnvironmentFast-paced startup, collaborative teamsVaries; startups or corporate settings, collaborative
Industry UsageCommon in tech startups focusing on AI/ML productsWidespread across tech, finance, healthcare
Search & Comparison IntentInterested in ML-specific roles in startupsLooking for data analysis or data science internships

Internship Machine Learning Startup roles focus on applying ML techniques in startup environments, often requiring programming and statistical skills. Data Science Internships may encompass broader data analysis tasks across various industries. Both roles share similar credentials and work environments, but ML internships are more specialized in machine learning applications within startups.

What are popular job titles related to Internship Machine Learning Startup jobs in Kansas? For Internship Machine Learning Startup jobs in Kansas, the most frequently searched job titles are:
What cities in Kansas are hiring for Internship Machine Learning Startup jobs? Cities in Kansas with the most Internship Machine Learning Startup job openings:
Research Engineer - Machine Learning & Robotics

Research Engineer - Machine Learning & Robotics

Jumio

Lenexa, KS

Other

Posted 20 days ago


Job description

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.