AI Intern - DataOps
Austin, TX
Apptronik
Apptronik is building robots for the real world to improve human quality of life and to help solve the ever-increasing labor shortage problem. Our team has been building some of the most advanced robots on the planet for years, dating back to the DARPA Robotics Challenge. We apply our expertise across the full robotics stack to some of the most important and impactful problems our society faces, and expect our products and technology to change the world for the better. We value passion, creativity, and collaboration to help us overcome existing technological barriers in the industry to create truly innovative products.
You will join a team developing state-of-the-art general-purpose robots designed to operate in human spaces and with human tools. It is designed to work alongside humans, mobilize to human spaces, and manipulate the world around it.
JOB SUMMARY
As an intern on the Apptronik AI Robotics Data team (AIROps/DataOps), you will contribute by delivering high-quality data to drive frontier model performance. We collaborate closely with the post-training team and Robot Park team to develop new solutions that accelerate research progress across model capabilities, evaluation, and safety.
WHAT TO EXPECT
This position is expected to start in-person around May/June 2025 and continue through the entire Summer (i.e. through Aug/Sep 2025). We ask for a minimum of 10 weeks. Interns should expect to work Monday-Friday, up to 40 hours per week, typically between 9am-5pm. Specific team norms around working hours will be communicated by your manager. Please consider before applying.
ESSENTIAL DUTIES AND RESPONSIBILITIES or KEY ACCOUNTABILITIES
- Be responsible for architecting, building, and designing our data collection/management platform
- Iterate rapidly on new features to improve user experience on our platform for both human operations and our research team
- Build features end-to-end: front-end, back-end, system design, debugging and testing
- Build systems that monitor and flag quality issues with large-scale data collections
- Establish best practices and help scale a world-class engineering team
- Ensure that our overall data collection platform is secure, scalable, and delightful to use.
- Innovating new ideas that bring us closer to our goal: to develop a world class AI-enabled humanoid robot platform.
TECH STACK
- Typescript, Python, Rust, C/C++
- React, Express, PostgreSQL
EDUCATION and/or EXPERIENCE
- MUST be an MS or PhD student enrolled in an accredited academic program during the internship term located in the United States. (New graduates not enrolled in an accredited program for Fall 2025 are ineligible.)
- Pursuing a degree in Computer Science, Machine Learning, Engineering, Robotics, or a related field
- Demonstrated track record. The portfolio can consist of: code, technical writing (white papers or blog posts), peer reviewed papers in Tier-1 Machine Learning, Robotics and Computer Vision
- Proficiency in Python, C++, CUDA, or another systems programming language
- Writing scalable and highly available containerized applications.
- MLOps Tooling for data lifecycle management
PHYSICAL REQUIREMENTS
- Prolonged periods of sitting at a desk and working on a computer
- Must be able to lift 15 pounds at times
- Vision to read printed materials and a computer screen
- Hearing and speech to communicate
*This is a direct hire. Please, no outside Agency solicitations.
Apptronik provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
Tags: Computer Science Computer Vision CUDA DataOps Engineering Machine Learning MLOps PhD PostgreSQL Python React Research Robotics Rust Testing TypeScript
More jobs like this
Explore more career opportunities
Find even more open roles below ordered by popularity of job title or skills/products/technologies used.