At a Glance
- Tasks: Develop machine learning systems for next-gen robotics, focusing on perception and decision-making.
- Company: Innovative UK-based robotics company transforming industrial automation.
- Benefits: Remote work, competitive salary, and opportunities for professional growth.
- Other info: Join a dynamic team tackling complex engineering challenges in robotics.
- Why this job: Make a real impact in robotics by applying cutting-edge machine learning techniques.
- 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 is required.
- 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 (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 strong 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 continuous learning and development. The remote work flexibility allows for a balanced lifestyle, making it an attractive choice for those looking to make a meaningful impact in the rapidly evolving field of industrial automation.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer (Remote) in Aylesbury
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. We can’t stress enough how important it is to build relationships; you never know who might have the inside scoop on job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and robotics. We love seeing practical applications of your work, so make sure to highlight any real-world impact your projects have had.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and ML concepts. Practice common algorithms and data structures, and be ready to discuss your past projects in detail. We want to see how you think and solve problems!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always looking for passionate individuals who want to make a difference in the robotics space, so don’t hesitate to put yourself out there!
We think you need these skills to ace Machine Learning Engineer (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 C++. If you’ve worked with deep learning frameworks or cloud infrastructure, make sure to include that too. We want to see your technical prowess!
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, especially those related to robotics and computer vision. Be ready to discuss your experience with deep learning, neural networks, and any relevant projects you've worked on. This is your chance to show how your skills align with the company's focus on building production-ready ML systems.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific 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 complex problems in real-world environments.
✨Familiarise Yourself with Their Tech Stack
Get to know the tools and technologies mentioned in the job description, like Python, C++, cloud infrastructure, and MLOps workflows. If you have experience with Docker, CI/CD pipelines, or ROS/ROS2, make sure to highlight that. Showing that you're comfortable with their tech stack will give you an edge.
✨Ask Insightful Questions
Prepare some thoughtful questions about the company's projects, team dynamics, and future goals. This not only shows your genuine interest in the role but also gives you a better understanding of how you can contribute to their mission of transforming industrial automation. Plus, it’s a great way to engage with your interviewers!
