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- Tasks: Design and train reinforcement learning policies for humanoid robots.
- Company: Join Humanoid, a leader in robotic innovation and technology.
- Benefits: Competitive pay, free meals, and hands-on experience with real robots.
- Other info: Full-time summer internship in a dynamic London office.
- Why this job: Make a real impact on the future of robotics while learning from experts.
- Qualifications: Experience with PyTorch, coding skills, and a passion for robotics.
The predicted salary is between 20000 - 30000 £ per year.
Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially‑scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 Alpha – our rapidly developed humanoid platform now running in real industrial pilots – and we’re growing the team to take it even further.
The Opportunity
We’re looking for interns who are curious, hands‑on, and excited to work directly with robotic systems. This is an open‑ended internship where you will design and train reinforcement learning policies that enable dynamic locomotion and loco‑manipulation behaviors on real robots. Your work will focus on building scalable training pipelines, designing reward functions and environments, and improving sim‑to‑real transfer for reliable deployment on hardware. You will work closely with control and robotics engineers to integrate learned policies into the robot control stack, ensuring stable and robust behavior in real‑world conditions.
This is a full‑time internship (5 days per week) over the summer (mid June - mid September), based in our London Paddington office, where you’ll contribute to real robotic systems from early on with guidance from experienced engineers. Duration: 12 weeks | Start date: June | Compensation: Competitive pay + we’ll keep you fed (seriously, our breakfasts and lunches are good).
What you might work on:
- Design and train reinforcement learning policies for humanoid robot control
- Build scalable simulation and training pipelines (e.g., Isaac Lab, MuJoCo)
- Design reward functions, observation spaces, and curricula for complex behaviors
- Run and analyse existing policies
- Identify issues, troubleshoot, and propose creative solutions
- Document procedures and findings, helping shape the evolution of our humanoids
What we’re looking for:
- Hands‑on experience with PyTorch and training ML models
- Strong interest in reinforcement learning, machine learning and robotics
- Experience writing code (e.g. Python, C++, or similar)
- Comfortable working with hardware, experiments, and debugging
- Ability to learn quickly and operate in a fast‑paced environment
- Problem‑solving mindset and attention to detail
- Clear communication and ability to work closely with a team
Internship - Controls employer: Humanoid
Contact Detail:
Humanoid Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Internship - Controls
✨Tip Number 1
Get hands-on! If you can, try to work on personal projects or contribute to open-source robotics initiatives. This will not only boost your skills but also give you something tangible to discuss during interviews.
✨Tip Number 2
Network like a pro! Attend robotics meetups, workshops, or online webinars. Connecting with industry professionals can lead to insider tips and even job opportunities that aren’t advertised.
✨Tip Number 3
Show your passion for robotics! When you get the chance to chat with potential employers, share your excitement about the field and any relevant experiences. It’s all about making a memorable impression!
✨Tip Number 4
Apply through our website! We’re always on the lookout for curious minds ready to dive into the world of robotics. Don’t miss out on the chance to join us at Humanoid and make a real impact!
We think you need these skills to ace Internship - Controls
Some tips for your application 🫡
Show Your Passion for Robotics: When you're writing your application, let your enthusiasm for robotics shine through! We want to see that you're genuinely excited about working with humanoid robots and how they can amplify human potential. Share any relevant projects or experiences that highlight your curiosity and hands-on skills.
Tailor Your Application: Make sure to customise your application to fit the internship role. Highlight your experience with reinforcement learning, machine learning, and any coding skills you have in Python or C++. This shows us that you've done your homework and understand what we're looking for!
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and make sure your key skills and experiences are easy to spot. A well-structured application helps us see your potential quickly!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it makes the whole process smoother for everyone involved!
How to prepare for a job interview at Humanoid
✨Know Your Stuff
Make sure you brush up on reinforcement learning and the specific technologies mentioned in the job description, like PyTorch. Familiarise yourself with how these concepts apply to robotics, as it’ll show your genuine interest and understanding during the interview.
✨Show Off Your Hands-On Experience
Be ready to discuss any practical projects or experiences you've had with coding, especially in Python or C++. If you've worked on simulations or training pipelines before, share those stories! Real-world examples will make you stand out.
✨Ask Smart Questions
Prepare thoughtful questions about the team’s current projects or challenges they face with their humanoid robots. This not only shows your enthusiasm but also your critical thinking skills and willingness to engage with the team.
✨Demonstrate Team Spirit
Since collaboration is key in this role, be sure to highlight your ability to work well in a team. Share examples of how you've successfully collaborated on projects in the past, and express your excitement about contributing to a team environment.