Join ANYbotics as a Reinforcement Learning intern to advance robotic navigation capabilities in a fast-paced environment.
Posted by employer 4 months ago
First seen on Joblaze 1 day ago
Last verified on the company career page 1 day ago
What you'll build
- Evaluate and fine-tune RL-based navigation policies
- Integrate ML models into ANYmal
- Collaborate with robotics experts
- Work on real quadruped robots
Practical constraints
- Full-time internship lasts six months
- Preferred starting date is September 2026
AI in the day-to-day
Utilizing the latest reinforcement learning techniques and simulation tools to define, train, and integrate ML models.
Not disclosed in this posting: compensation, years of experience, work arrangement, visa sponsorship.
Joblaze summary
The intern in Reinforcement Learning for Navigation will focus on enhancing the mobility of ANYbotics' quadruped robot, ANYmal, by developing and refining machine learning models for navigation in complex environments. Key skills include expertise in reinforcement learning, simulation tools, and robotics, with a strong emphasis on practical application. This role is ideal for individuals with a background in machine learning or robotics, particularly those seeking hands-on experience in a fast-paced tech environment. The intern will collaborate closely with experts and research partners, gaining valuable insights and mentorship.
Joblaze insights
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Listed yesterday
— first seen on Joblaze November 8, 2026.
Last confirmed on ANYbotics's careers page November 8, 2026.
Quick facts
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AI, Computer Vision, Machine Learning, Robotics, reinforcement learning.
- What seniority level is this role?
- ANYbotics targets intern candidates for this position.
- Is this full-time or contract?
- Internship for this Internship - Reinforcement Learning for Navigation role at ANYbotics.
From the original posting
ANYbotics is a fast-growing tech company dedicated to shaping the future of mobile robotics across multiple industries. Join our highly talented and motivated team of more than 190 people and work on cutting-edge robot technology. We are open to internships all year round and post regularly.
We’re always looking for passionate, curious, and motivated interns to join our mission.
This is your chance to collaborate with world-class experts, gain real-world experience, and make meaningful contributions in a fast-paced, interdisciplinary environment.
We’re always looking for passionate, curious, and motivated interns to join the Advanced Technology team. We explore emerging technologies and transform them into practical innovations that shape the future of robotics at ANYbotics. We bridge cutting-edge research with real-world industrial applications by rapidly validating new ideas, building prototypes, and transferring successful technologies into our products. Working closely with leading universities, startups, and internal engineering teams, we tackle challenging problems in robotics, AI, computer vision, and autonomous systems to create the next generation of industrial inspection robots.
The Opportunity
We are looking for a Reinforcement Learning for Robotic Navigation intern to join our Advanced Technology team and contribute to advancing ANYmal's mobility capabilities. Utilizing the latest reinforcement learning techniques and simulation tools, we define, train, and integrate ML models into ANYmal to safely and robustly navigate challenging industrial environments.
Your role includes evaluating and fine tuning state of the art RL-based navigation & locomotion policies in simulation and on real quadruped robots. This internship provides a profound and impactful opportunity to work at the forefront of machine learning in robotics, playing a significant role in shaping ANYmal's autonomous capabilities and contributing to real-world applications.
You will work closely with Robotics experts and research partners who will provide you with guidance and mentorship. The preferred starting date is September 2026, and the full-time paid internship lasts six months.