At a Glance
- Tasks: Develop machine learning systems for next-gen robotics and optimise real-world applications.
- Company: Innovative UK robotics company transforming industrial automation.
- Benefits: Hybrid 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 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 - Hybrid Remote 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 a hybrid remote work model that promotes work-life balance. 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 robotics.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer - Hybrid Remote
✨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 local tech events. 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 evidence of your work can really set you apart from the crowd.
✨Tip Number 3
Don’t just apply blindly! Tailor your approach for each application. Research the company and mention specific projects or values that resonate with you. This shows you're genuinely interested and not just sending out cookie-cutter applications.
✨Tip Number 4
Apply through our website! We love seeing candidates who take the initiative to reach out directly. Plus, it gives you a better chance to stand out in the hiring process. So, don’t hesitate – hit that apply button!
We think you need these skills to ace Machine Learning Engineer - Hybrid Remote
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 expertise in machine learning, robotics, and any relevant projects you've worked on. We want to see how you can contribute to our mission!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about robotics and machine learning. Share specific examples of how you've tackled complex challenges in the past, and let us know why you want to join our team.
Showcase Your Projects:If you've worked on any interesting projects related to machine learning or robotics, make sure to include them in your application. We love seeing practical applications of your skills, so don't hold back on sharing your achievements!
Apply Through Our Website:We encourage you to apply directly 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 past projects and how you've applied these concepts 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. This company values innovative thinking, so think beyond just incremental improvements and be ready to share your creative solutions.
✨Familiarise Yourself with Their Tech Stack
Get to know the tools and technologies mentioned in the job description, like Python, C++, and cloud-based training infrastructure. If you have experience with Docker, CI/CD pipelines, or ROS/ROS2, make sure to highlight that during the interview.
✨Ask Insightful Questions
Prepare some thoughtful questions about the company's robotics platform and their approach to machine learning. This shows your genuine interest in the role and helps you understand how you can contribute to their mission.
