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- Tasks: Train cutting-edge RL policies for humanoid robots and tackle real-world challenges.
- Company: Join Humanoid, the UK's pioneering AI and robotics company.
- Benefits: Competitive salary, stock options, paid vacation, and travel opportunities.
- Why this job: Be part of a revolutionary mission to enhance human capabilities with advanced robotics.
- Qualifications: 3+ years in deep learning, strong Python skills, and RL experience.
- Other info: Enjoy a startup culture with free meals, team events, and minimal bureaucracy.
The predicted salary is between 36000 - 60000 £ per year.
Humanoid is the first AI and robotics company in the UK, creating the world’s most advanced, reliable, commercially scalable, and safe humanoid robots. Our first humanoid robot HMND 01 is a next-gen labour automation unit, providing highly efficient services across various use cases, starting with industrial applications.
Our Mission
At Humanoid we strive to create the world’s leading, commercially scalable, safe, and advanced humanoid robots that seamlessly integrate into daily life and amplify human capacity.
Vision
In a world where artificial intelligence opens up new horizons, our faith in its potential unveils a new outlook where, together, humans and machines build a new future filled with knowledge, inspiration, and incredible discoveries. The development of a functional humanoid robot underpins an era of abundance and well-being where poverty will disappear, and people will be able to choose what they want to do. We believe that providing a universal basic income will eventually be a true evolution of our civilization.
Solution
As the demands on our built environment rise, labour shortages loom. With the world’s workforce increasingly moving away from undesirable tasks, the manufacturing, construction, and logistics industries critical to our daily lives are left exposed. By deploying our general-purpose humanoid robots in environments deemed hazardous or monotonous, we envision a future where human well-being is safeguarded while closing the gaps in critical global labour needs.
What You’ll Do
Train language-vision conditioned manipulation policies via reinforcement learning (RL) in simulation and in the real world. Construct challenging and diverse suites of manipulation tasks in simulation. Partner with teleoperations to collect trajectories in simulation for behaviour cloning. Partner with testing and operations to establish real-world RL training pipelines. Experiment with various ways of bringing policies trained in simulation to the real world.
We’re Looking For
3+ years building deep-learning systems (industry or research) with shipped models or published artifacts to show for it. Hands-on with at least one of: LLMs, VLMs, or image/video generative models — architecture, training, and inference. Experience solving real problems using reinforcement learning with deep neural networks in any domain. Strong Python + PyTorch/JAX; you can profile, debug numerics, and write maintainable research code. You are self-driven, pro-active, communicate efficiently, document experiments clearly and communicate trade-offs crisply.
Nice to have
Experience with simulators for robotics (Isaac Sim, MuJoCo etc.). Experience in RL for robotics. Experience building infrastructure for large-scale RL (e.g. using ray). Publications at ICLR/ICML/NeurIPS or equivalent open-source contributions. Familiarity with OpenVLA, Physical Intelligence (Ï€) models, or similar open VLA frameworks.
What We Offer
Competitive salary plus participation in our Stock Option Plan. Paid vacation with adjustments based on your location to comply with local labour laws, and additional paid sick leave days. Travel opportunities to our Vancouver and Boston offices. Office perks: free breakfasts, lunches, snacks, and regular team events. Freedom to influence the product and own key initiatives. Collaboration with top-tier engineers, researchers, and product experts in AI and robotics. Startup culture prioritising speed, transparency, and minimal bureaucracy.
How to Apply
Does this role sound like the perfect fit for you? Fill in the form and include links or files that showcase the best of what you’ve built and achieved.
Reinforcement Learning (RL) Engineer, Manipulation employer: Humanoid
Contact Detail:
Humanoid Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Reinforcement Learning (RL) Engineer, Manipulation
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and robotics space, especially those who work at Humanoid. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Create a portfolio or a GitHub repo showcasing your projects related to reinforcement learning and deep learning. This is your chance to shine and demonstrate what you can bring to the table.
✨Tip Number 3
Prepare for the interview by brushing up on your technical knowledge and problem-solving skills. Practice explaining your past projects clearly and concisely, focusing on how they relate to the role of an RL Engineer.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining our mission at Humanoid.
We think you need these skills to ace Reinforcement Learning (RL) Engineer, Manipulation
Some tips for your application 🫡
Showcase Your Experience: Make sure to highlight your 3+ years of experience in building deep-learning systems. Include any shipped models or published work that demonstrates your skills, especially in reinforcement learning and deep neural networks.
Be Clear and Concise: When filling out the application form, keep your descriptions clear and to the point. We love candidates who can communicate their ideas crisply, so make sure to document your experiments and trade-offs effectively.
Link Your Work: Don’t forget to include links or files that showcase your best projects! Whether it’s GitHub repos or research papers, we want to see what you’ve achieved and how it relates to the role.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Humanoid
✨Know Your Stuff
Make sure you brush up on your reinforcement learning concepts and the specific technologies mentioned in the job description, like deep learning systems and Python frameworks. Be ready to discuss your past projects and how they relate to the role.
✨Showcase Your Experience
Prepare to talk about your hands-on experience with LLMs, VLMs, or generative models. Bring examples of your work, whether it's shipped models or published papers, to demonstrate your expertise and problem-solving skills.
✨Be Ready for Technical Questions
Expect technical questions that dive deep into your knowledge of RL and robotics. Practice explaining complex concepts clearly and concisely, as communication is key in this role. Think about how you can articulate trade-offs in your previous projects.
✨Cultural Fit Matters
Humanoid values a startup culture, so be prepared to discuss how you thrive in fast-paced environments. Share examples of how you've collaborated with teams, influenced product decisions, and adapted to changes quickly. Show them you're not just a tech whiz but also a great team player!
