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- Tasks: Design, train, and deploy multitask manipulation policies for advanced robotics.
- Company: Kinisi Robotics is innovating in dexterous manipulation and robotic learning.
- Benefits: Enjoy a hybrid work model with opportunities for hands-on experience and collaboration.
- Why this job: Join a team shaping the future of industrial automation with cutting-edge technology.
- Qualifications: M.S. in CS, ML, Robotics or related field; hands-on experience with control policies required.
- Other info: Work primarily on-site in Bristol, UK, with a focus on real-world applications.
The predicted salary is between 42000 - 84000 £ per year.
Location: Bristol, UK | Hybrid (primarily on-site)
Team: Manipulation & Robot Learning Team
Employment Type: Full-time, Permanent
About the Role
Kinisi is pushing the frontier of dexterous, whole-body manipulation. By fusing large-scale demonstration data - from teleoperation, human demos and the open web - we teach Kinisi robots to solve new tasks from just a handful of examples. As an Large-Behaviour Models Engineer, you’ll help design, train and ship the next generation of multitask manipulation policies.
What You’ll Do
- Invent & apply ML – Turn cutting-edge behaviour-cloning and generative-model ideas into practical solutions for real, bimanual manipulation challenges.
- Build great software – Craft well-documented, tested and maintainable Python / C++ code that the whole team can rely on.
- Drive technical direction – Lead design reviews and partner closely with Kinisi-platform engineers to integrate your work end-to-end.
- Own deployment – Bring your models onto Kinisi hardware, debug in the loop and iterate until performance shines.
Qualifications
- M.S. (or higher) in CS, ML, Robotics or a related field.
- Hands-on experience training and rolling out learned control policies - either on robots or complex simulated agents.
- Fluency with modern ML stacks, model architectures and experiment workflows.
- Sharp analytical instincts and a knack for diagnosing tricky runtime issues.
Why Join Us?
This is an opportunity to work on cutting-edge robotic systems in a collaborative, hands-on environment. You’ll contribute to a product that’s heading to market and help shape the future of industrial automation.
Large Behaviour Models Research Engineer employer: Kinisi Robotics
Contact Detail:
Kinisi Robotics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Large Behaviour Models Research Engineer
✨Tip Number 1
Familiarise yourself with the latest advancements in behaviour cloning and generative models. Being able to discuss recent research or breakthroughs in these areas during your interview will show your passion and expertise.
✨Tip Number 2
Prepare to demonstrate your coding skills in Python and C++. Consider working on a small project that showcases your ability to write clean, maintainable code, as this could be a topic of discussion during technical interviews.
✨Tip Number 3
Brush up on your knowledge of machine learning stacks and experiment workflows. Be ready to explain how you've used these tools in past projects, as practical experience is highly valued in this role.
✨Tip Number 4
Network with professionals in the robotics and machine learning fields. Attend relevant meetups or online forums where you can connect with others who might have insights into Kinisi Robotics or similar companies.
We think you need these skills to ace Large Behaviour Models Research Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, robotics, and software development. Emphasise any hands-on projects or roles where you've trained control policies or worked with Python/C++.
Craft a Compelling Cover Letter: In your cover letter, express your passion for robotics and manipulation technologies. Mention specific projects or experiences that align with Kinisi's goals and how you can contribute to their team.
Showcase Your Technical Skills: Include examples of your work with modern ML stacks and model architectures. If possible, provide links to GitHub repositories or projects that demonstrate your coding abilities and problem-solving skills.
Prepare for Technical Questions: Anticipate technical questions related to machine learning and robotics during the interview process. Brush up on your knowledge of behaviour-cloning, generative models, and debugging techniques to impress the hiring team.
How to prepare for a job interview at Kinisi Robotics
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning, particularly in behaviour cloning and generative models. Highlight specific projects where you've applied these techniques, especially in the context of robotics or complex simulations.
✨Demonstrate Problem-Solving Abilities
Expect questions that assess your analytical skills and how you approach diagnosing runtime issues. Prepare examples of challenges you've faced in previous roles and how you resolved them, particularly in relation to deploying models on hardware.
✨Familiarise Yourself with Their Technology
Research Kinisi's current projects and technologies. Understanding their manipulation systems and how they integrate machine learning will show your genuine interest and help you engage in meaningful discussions during the interview.
✨Prepare for Collaborative Scenarios
Since the role involves working closely with platform engineers, be ready to discuss your experience in collaborative environments. Think of examples where you've led design reviews or partnered with others to achieve a common goal.
