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- Tasks: Develop cutting-edge RL models for intelligent robotic platforms and bridge simulation with real-world applications.
- Company: High-profile robotics organisation in Central London with a collaborative culture.
- Benefits: Competitive salary, fantastic benefits, and access to cutting-edge hardware.
- Why this job: Join a pioneering team and make a real impact on the future of AI and robotics.
- Qualifications: 5+ years in deep learning, with expertise in RL and practical robotics experience.
- Other info: Dynamic environment with opportunities for professional growth and innovation.
The predicted salary is between 43200 - 72000 £ per year.
A high-profile robotics organization is urgently seeking a high-calibre RL Engineer (Manipulation) to join their London-based R&D team. This role is pivotal in bridging the gap between simulation and real-world application, focusing on the development of language-vision conditioned policies for next-generation intelligent robotic platforms.
Responsibilities
- Sim-to-Real Transfer: Developing manipulation tasks in simulators (Isaac Sim/MuJoCo) and successfully deploying trained policies onto physical hardware.
- VLA Policy Development: Training Vision-Language-Action models via RL to enable robots to execute actions based on visual and linguistic context.
- Trajectory Scaling: Collaborating with teleops teams to transform human trajectories into robust robotic skills through behaviour cloning.
- High-Performance Engineering: Designing and profiling research-grade PyTorch/JAX code to support large-scale, distributed RL infrastructure.
Qualifications
- Deep Learning Mastery: 5+ years building and shipping models, with deep hands-on expertise in LLMs, VLMs, or generative architectures.
- Industry Experience: 3+ years of commercial experience delivering production-grade AI solutions.
- RL Expert: A proven track record of solving complex, real-world problems using Deep Reinforcement Learning.
- Technical Rigour: Mastery of Python and PyTorch/JAX, including the ability to profile performance and debug complex numerical stability issues.
- Robotics Foundation: Practical experience with simulators (Isaac Sim/MuJoCo) and a deep understanding of sim-to-real bottlenecks.
Competitive Package | Central London | 5 days in office | collaborative working environment | fantastic benefits | Cutting-Edge Hardware
If you are looking to join a high-profile robotics organization and make a tangible impact on the future of LLMs and Embodied AI, this is the ideal opportunity for you. To discuss this role further, please apply directly to this advert or send your CV to (see below).
Reinforcement Learning (RL) Control Engineer employer: Randstad Technologies
Contact Detail:
Randstad Technologies Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Reinforcement Learning (RL) Control Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the robotics and AI field on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving RL and manipulation tasks. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice explaining complex concepts in simple terms – it shows you really understand your stuff!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love hearing from passionate candidates like you!
We think you need these skills to ace Reinforcement Learning (RL) Control Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with RL and robotics. We want to see how your skills match the job description, so don’t be shy about showcasing your relevant projects and achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about RL and how you can contribute to our team. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Technical Skills: Since this role requires deep learning mastery, make sure to mention your experience with Python, PyTorch, and any simulators like Isaac Sim or MuJoCo. We’re looking for those specific skills, so highlight them clearly!
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’re considered for this exciting opportunity. Don’t miss out!
How to prepare for a job interview at Randstad Technologies
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technical skills listed in the job description, especially Python and PyTorch/JAX. Brush up on your knowledge of sim-to-real transfer and be ready to discuss specific projects where you've tackled these challenges.
✨Showcase Your Problem-Solving Skills
Prepare examples of complex problems you've solved using Deep Reinforcement Learning. Be ready to explain your thought process and the impact of your solutions, as this will demonstrate your expertise and ability to apply your knowledge in real-world scenarios.
✨Familiarise Yourself with Their Work
Research the company’s recent projects and innovations in robotics. Understanding their focus on language-vision conditioned policies will help you tailor your responses and show genuine interest in their work during the interview.
✨Practice Clear Communication
Since the role involves collaboration with teleops teams, practice explaining complex concepts in a simple way. Being able to communicate your ideas clearly will be crucial, especially when discussing trajectory scaling and behaviour cloning.
