At a Glance
- Tasks: Develop machine learning systems for next-gen robotics and optimise real-world applications.
- Company: Innovative UK-based robotics company transforming industrial automation.
- Benefits: Hybrid or remote work, competitive salary, and exposure to cutting-edge technology.
- Other info: Join a highly technical team and grow your career in a rapidly evolving field.
- Why this job: Make a tangible impact in robotics and tackle complex engineering challenges.
- Qualifications: Experience in machine learning, computer vision, and production ML systems.
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. 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 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.
The ideal candidate will have a strong background in applied machine learning, computer vision, or robotics engineering, alongside experience building production ML systems:
- 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 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
- Additional experience with GPU acceleration, edge deployment, ROS/ROS2, Docker, CI/CD pipelines, or robotics integration would be highly advantageous.
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 (hybrid or remote) in Aylesbury employer: Findrs
This UK-based robotics company is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration among highly skilled professionals. With a focus on employee growth, the company provides opportunities to engage in cutting-edge projects at the intersection of machine learning and robotics, while also supporting flexible working arrangements. Employees benefit from a supportive environment that encourages creativity and the application of modern techniques to solve complex industrial challenges, making it an ideal place for those looking to make a meaningful impact in the field of automation.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer (hybrid or remote) in Aylesbury
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the robotics and machine learning scene. Attend meetups, webinars, or even online forums. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨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 interviews by diving deep into the company’s tech stack and recent projects. Be ready to discuss how your experience aligns with their goals, especially around building scalable ML systems and integrating them into robotics. Tailor your responses to show you’re the perfect fit!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented individuals like you. Plus, it’s a great way to ensure your application gets seen by the right people. Let’s get you on board!
We think you need these skills to ace Machine Learning Engineer (hybrid or remote) in Aylesbury
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the job description. Highlight your machine learning projects, especially those related to robotics and computer vision, to show us you’re the right fit!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about robotics and machine learning. Share specific examples of how you've tackled complex challenges in the past, and let your enthusiasm shine through!
Showcase Your Technical Skills:Don’t forget to mention your programming skills, especially in Python and any experience with C++. If you’ve worked with cloud infrastructure or MLOps workflows, make sure to include that too – we love seeing relevant technical expertise!
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 during the process!
How to prepare for a job interview at Findrs
✨Know Your Stuff
Make sure you brush up on the latest machine learning techniques and frameworks relevant to the role. Be ready to discuss your experience with deep learning, computer vision, and any specific projects you've worked on that relate to robotics. This shows you're not just familiar with theory but can apply it in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare to talk about complex challenges you've faced in previous roles and how you tackled them. The company is looking for someone who can think beyond incremental improvements, so be ready to share examples of how you've applied modern ML techniques to solve tough industrial problems.
✨Get Technical
Since this role involves building production-ready ML systems, be prepared to dive into technical discussions. Brush up on your Python and C++ skills, and be ready to explain your experience with scalable ML systems, cloud infrastructure, and MLOps workflows. They’ll want to know you can handle the technical demands of the job.
✨Ask Insightful Questions
Interviews are a two-way street, so come armed with questions that show your interest in the company's technology and future direction. Ask about their current projects, the challenges they face in robotics integration, or how they envision the evolution of their ML systems. This demonstrates your enthusiasm and helps you gauge if the company is the right fit for you.
