At a Glance
- Tasks: Develop cutting-edge control systems for autonomous excavation machines in real-world environments.
- Company: Gravis Robotics, a fast-growing startup revolutionising construction with intelligent robotics.
- Benefits: Competitive salary, mentorship opportunities, and a chance to work on groundbreaking technology.
- Other info: Collaborative environment with opportunities for career growth and innovation.
- Why this job: Join a dynamic team and make a tangible impact in the trillion-dollar construction industry.
- Qualifications: 2-5 years in reinforcement learning, strong Python and C++ skills, and real robot deployment experience.
The predicted salary is between 59400 - 72600 £ per year.
Gravis Robotics is a startup turning heavy construction machines into intelligent and autonomous robots. Our unique combination of learning-based automation and augmented remote control enables a single operator to safely manage a fleet of earthmoving machines in a gamified environment. With over a decade of academic experience at the cutting edge of large-scale robotics, our team is rapidly translating this expertise into real-world deployments with industry leaders in a trillion-dollar market. Our Rooftop Autonomous Control Kit (RACK) integrates sensing, compute, communication, and networking into a manufacturer-agnostic solution that works across a wide range of construction machines. We operate at the intersection of hardware, software, and real-world deployment, and we're growing fast.
The autonomy team at Gravis builds autonomous systems for excavators operating in real construction environments. You will build control modules that run on many different machines, across many sites, with different soil conditions. We’re looking for a roboticist with data driven planning and/or control background, deep Python expertise and good level of C++ proficiency.
To thrive in this role, you should have experience working with physical robots, navigating the challenges of sim-to-real (sim2real) transfer, and deploying robotic systems into production environments.
What You Will Do
- Develop data driven planning and control systems for autonomous excavation that generalize across machine models and soil conditions.
- Contribute to simulation improvements that reduce or address the sim2real gap.
- Define data collection and curation pipelines for incorporating real data in policy training.
- Design experiments focused on continuous performance and robustness improvements.
- Explore the usage of adaptive and online reinforcement learning in deployed systems.
- Provide mentorship and supervision for junior team members, interns, and students.
System Integration
- Integrate learned components into a larger software stack.
- Collaborate with excavation and motion planning engineers.
- Build tools for analysing and evaluating the behavior of learned components.
What We’re Looking For
We recognize that excellent candidates come from diverse backgrounds with various combinations of skills. If you meet most of the core qualifications below, we highly encourage you to apply.
Core Qualifications
- 2-5 years industry experience developing Reinforcement learning systems for control and/or planning and deploying them on real robots with a customer. If you only have experience with simulation, you’re most likely not a good fit for this position.
- Experience with GPU accelerated simulation environments (e.g. IsaacSim/IsaacLab, CARLA, MuJoCo).
- Strong Python skills and experience with PyTorch or similar libraries.
- Proficiency in C++.
- Comfortable debugging real-world system behavior.
- Ability and willingness to travel as required by business projects.
Senior Reinforcement Learning Engineer employer: Gravis-Robotics
Gravis Robotics is an exceptional employer for those passionate about cutting-edge technology and innovation in the field of robotics. With a dynamic startup culture that encourages creativity and collaboration, employees benefit from hands-on experience in real-world deployments while enjoying flexible remote work options. The company prioritises professional growth, offering opportunities to lead impactful projects and engage directly with industry leaders, all within the vibrant Manchester–London corridor.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Reinforcement Learning Engineer
✨Dive into Robotics Meetups
Get yourself out there and connect with others in the robotics-automation field by attending local meetups and industry events. These gatherings are where the magic happens, and you might just rub shoulders with someone from Gravis-Robotics or get insider tips on upcoming vacancies.
✨Showcase Your Projects
Create a portfolio that highlights your robotics projects, whether they're personal, academic, or freelance. Share this on platforms like GitHub or your personal website, as it shows potential employers, like Gravis-Robotics, what you're made of and your hands-on experience in the field.
✨Utilise University Resources
If you're fresh out of university or still connected, don't underestimate your career services. They often have exclusive access to job fairs and employer networking events in technical fields like ours, so make sure you tap into those resources to discover openings at companies like Gravis-Robotics.
✨Engage in Online Communities
Join online communities that focus on robotics and automation, such as forums or LinkedIn groups. Engage in conversations, ask questions, and share insights. This not only builds your visibility but could also lead to direct connections at firms like Gravis-Robotics, which might have the full-time role you're after.
We think you need these skills to ace Senior Reinforcement Learning Engineer
Some tips for your application 🫡
Showcase Your Technical Skills:In the robotics and automation field, it's crucial to highlight your technical skills on your CV. Include specific programming languages, software platforms, and any relevant robotics experience. Don’t forget to mention any projects or systems you've developed – this info can really make you stand out!
Portfolio Perfection:Having a polished portfolio can speak volumes for a role in robotics. Include any relevant case studies, designs, or prototypes you've worked on. If you've participated in competitions or hackathons, showcase these achievements as well – they show initiative and problem-solving skills!
Tailored Cover Letter Magic:In your cover letter, don’t just tell us that you love robotics—tell us why you’re passionate about automation specifically! Explain how your skills can contribute to Gravis-Robotics’s projects and remember to connect your past experiences to what you'll be doing in this role.
Certifications Matter:If you’ve got any relevant certifications, such as in robotic process automation or machine learning, make sure they’re front and centre on your CV. These credentials show you're dedicated to your field and keep you up to date with industry standards – we love to see that!
How to prepare for a job interview at Gravis-Robotics
✨Showcase Your Technical Wizardry
For a role in robotics and automation at Gravis-Robotics, it's crucial to demonstrate your technical skills. Be prepared to dive into specifics about the programming languages and tools you’ve used, like Python or ROS (Robot Operating System). Brush up on your knowledge of algorithms and control systems, as these might come up during technical questions.
✨Bring Your Projects to Life
With a full-time position in robotics, you should have a portfolio of your projects ready to show. Whether it's a robot you built for a competition or a simple automation script, make sure you can discuss the challenges you faced and how you solved them. This hands-on experience is gold and shows you can apply theoretical knowledge in real-world scenarios.
✨Think Like an Engineer
Expect some problem-solving scenarios during your interview. You might be asked to design a basic automation solution on the spot or troubleshoot a robotic system. Practising these types of technical questions can really set you apart, as they require critical thinking and a systematic approach to tackle problems.
✨Culture Fit Is Key!
Don’t underestimate the importance of cultural fit at Gravis-Robotics. They might ask about your teamwork experience and how you handle challenges with peers. Be ready to share examples of working in diverse teams, as collaboration is often central to projects in robotics and automation.
