At a Glance
- Tasks: Design, train, and optimise machine learning models for advanced robotics applications.
- Company: Innovative UK robotics company transforming industrial automation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Collaborate with a highly technical team on complex engineering challenges.
- Why this job: Join a team creating cutting-edge robotics technology with real-world impact.
- Qualifications: PhD or 2-5 years in machine learning, robotics, or computer vision.
The predicted salary is between 60000 - 80000 £ per year.
Build the Intelligence Behind Next Generation Robotics. Industrial robotics is evolving rapidly, but most robotic systems still struggle with fragmented integrations, unreliable perception, and limited scalability in real world environments. Our client is changing that. This UK based robotics company is building a next generation robotics platform designed to simplify deployment, improve operational intelligence, and accelerate automation across manufacturing and logistics environments. By combining robotics, machine learning, software engineering, and control systems, the company is creating robot agnostic technologies that transform industrial automation into a scalable, productised platform.
As the business continues to grow, they are now looking for an Applied Scientist / ML Engineer to help develop the machine learning systems powering the next generation of intelligent robotics. This is an opportunity for someone who enjoys taking cutting edge machine learning research and turning it into reliable, production grade systems that operate in demanding real world environments.
The Role
The successful candidate will play a critical role in designing, training, deploying, and optimising machine learning models used within advanced robotics applications. Working at the intersection of computer vision, robotics, and AI, they will develop deep learning systems that allow robots to perceive environments, understand scenes, process sensor inputs, and operate with greater reliability and precision. The company is particularly interested in individuals who can think beyond incremental improvements and apply modern machine learning techniques to solve complex industrial challenges. This includes leveraging foundation models, generative AI approaches, synthetic data generation, and scalable ML infrastructure to improve robotics capability and deployment speed.
A key responsibility will be developing robust neural network architectures focused on object detection, segmentation, pose estimation, and scene understanding. The successful candidate will work on models that directly impact robotic perception and decision making in live industrial environments. The role will also involve building scalable training and inference pipelines capable of supporting high performance production workloads. This includes fine tuning models, optimising inference performance, improving system reliability, and ensuring models can operate effectively in real time robotics applications.
In addition, the Applied Scientist / ML Engineer will contribute to the design and maintenance of data pipelines covering collection, ingestion, curation, versioning, and synthetic data generation. The ability to create scalable and maintainable ML workflows will be highly valuable as the company continues to expand its robotics platform. The successful candidate will work closely with robotics and software engineering teams to integrate machine learning systems into broader robotics pipelines. This includes working with distributed GPU training systems, cloud infrastructure, and edge deployment environments. Beyond technical delivery, the company is looking for someone who values strong engineering fundamentals and understands how to build production ready ML systems rather than isolated research prototypes. Testing, modular design, benchmarking, and maintainability will all be important parts of the role.
What They’re Looking For
The ideal candidate will have a strong background in applied machine learning, computer vision, or robotics engineering, alongside experience building production ML systems. Candidates should have:
- A PhD in Machine Learning, Robotics, Computer Vision, or a related field, or 2 to 5+ years of relevant industry experience
- Strong experience with deep learning and computer vision techniques
- A solid understanding of probability, optimisation, statistics, and ML fundamentals
- Strong Python programming skills, with C++ experience considered highly beneficial
- Experience using frameworks such as PyTorch, TensorFlow, or JAX
- Experience building scalable ML systems for production environments
- Familiarity with cloud or GPU based training infrastructure and MLOps workflows
- Experience designing evaluation, testing, and benchmarking frameworks
- Hands on experience with object detection, segmentation, pose estimation, camera calibration, and sensor integration
Additional experience with GPU acceleration, edge deployment, ROS/ROS2, Docker, CI/CD pipelines, or robotics integration would be highly advantageous.
Why Join?
This is an opportunity to join a business building genuinely innovative robotics technology with the potential to transform industrial automation on a global scale. The role offers exposure to complex engineering challenges across machine learning, robotics, computer vision, and distributed systems while working alongside a highly technical team developing real world robotics products. For ML engineers and applied scientists who want to move beyond pure research and build intelligent systems that directly power physical robotics platforms, this is an opportunity to make a tangible impact in a rapidly growing space.
Machine Learning Engineer employer: Findrs
Join a pioneering UK-based robotics company that is at the forefront of transforming industrial automation through innovative machine learning and robotics technology. With a strong emphasis on employee growth, collaborative work culture, and tackling complex engineering challenges, this role offers the chance to make a significant impact in a rapidly evolving field. Enjoy the benefits of working with a highly skilled team, access to cutting-edge resources, and the opportunity to contribute to scalable, production-grade systems that redefine the future of robotics.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Network like a pro! Get out there and connect with people in the robotics and machine learning space. Attend meetups, webinars, or industry conferences. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and robotics. Whether it's GitHub repos or a personal website, having tangible examples of your work can really set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your deep learning and computer vision knowledge. Practice coding challenges and system design questions that are relevant to the role. We recommend using platforms like LeetCode or HackerRank to sharpen your skills.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to engage with us directly. So, go ahead and hit that apply button!
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of Machine Learning Engineer. Highlight your experience with deep learning, computer vision, and any relevant projects that showcase your skills in building production ML systems.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about robotics and how your background aligns with our mission. Don’t forget to mention specific technologies or methodologies you’ve worked with that relate to the job.
Showcase Your Projects:If you've worked on any interesting projects, especially those involving robotics or machine learning, make sure to include them. We love seeing practical applications of your skills, so link to your GitHub or any relevant portfolios!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Findrs
✨Know Your Stuff
Make sure you brush up on your machine learning fundamentals, especially deep learning and computer vision techniques. Be ready to discuss your experience with frameworks like PyTorch or TensorFlow, and have examples of how you've built scalable ML systems in production.
✨Showcase Your Projects
Prepare to talk about specific projects where you've applied machine learning to solve real-world problems. Highlight your role in designing, training, and optimising models, especially in robotics applications. This will demonstrate your hands-on experience and ability to translate research into practical solutions.
✨Understand the Company’s Vision
Familiarise yourself with the company's mission to simplify deployment and improve operational intelligence in robotics. Think about how your skills can contribute to their goals, particularly in developing robust neural network architectures and scalable ML workflows.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in the role and the company. Inquire about their current challenges in integrating ML systems with robotics, or ask how they envision the future of industrial automation. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.
