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- Tasks: Design and implement machine learning pipelines for cutting-edge agricultural technology.
- Company: Innovative company revolutionising agriculture with intelligent systems.
- Benefits: Work on exciting projects with a supportive team in a dynamic environment.
- Other info: Onsite role in Newport Shropshire with excellent career growth opportunities.
- Why this job: Make a real impact on the future of agriculture through advanced technology.
- Qualifications: Experience in machine learning, computer vision, and proficiency in C, C++, Python.
The predicted salary is between 45000 - 60000 £ per year.
Are you ready to take your career to the next level by working on cutting-edge technology in the agricultural sector? This is your opportunity to be part of an innovative company that is revolutionising the way agriculture operates at their UK R&D facility. As a Machine Learning Engineer - Robotics & Perception, you will play a pivotal role in developing intelligent systems that are deployed in real-world environments, making a tangible impact on the industry. By helping design, train, and deploy perception systems — from image segmentation and object classification through to stereo camera pipelines and real-time deep neural inference. You will work closely with robotics, embedded, and systems engineers to bring cutting-edge vision intelligence into production agricultural environments.
What You Will Do:
- Design and implement machine learning pipelines for image segmentation, object detection, and 3D scene reconstruction.
- Train and optimise deep neural network models using frameworks such as PyTorch and TensorFlow.
- Manage and curate training datasets, including developing data augmentation and annotation strategies.
- Deploy machine learning models to embedded and edge computing platforms for real-time performance.
- Collaborate with cross-functional teams to integrate perception modules into broader system architectures.
- Maintain thorough documentation of model architectures, experiment results, and deployment procedures.
What You Will Bring:
- Proven experience in machine learning or computer vision engineering, with a strong understanding of CNN architectures such as YOLO.
- Proficiency in C, C++, Python and familiarity with Linux-based development environments.
- Knowledge of stereo vision pipelines, depth estimation, and geometric computer vision techniques.
- Experience in optimising and deploying models to constrained hardware environments.
- A PhD or degree in Computer Science, Electrical Engineering, Mechatronics, or equivalent industry experience.
By joining this company, you'll contribute to creating intelligent systems that are transforming agricultural practices. The role offers the chance to work on innovative projects alongside a supportive and talented team. This company values quality, continuous learning, and delivering real-world solutions that make a difference.
Location: This role is based onsite in Newport Shropshire, this position is commutable from Telford, Shrewsbury, Wolverhampton, Cannock and Bridgnorth.
Interested? Don't miss the chance to be part of this exciting journey. Apply today to become a Machine Learning Engineer - Robotics & Perception and help shape the future of intelligent agricultural technology!
Machine Learning Engineer - Robotics & Perception employer: Jonathan Lee Recruitment
Contact Detail:
Jonathan Lee Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer - Robotics & Perception
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and robotics. We recommend including links to GitHub or any relevant work that demonstrates your expertise in image segmentation and object detection.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. We suggest practising common machine learning scenarios and being ready to discuss your experience with frameworks like PyTorch and TensorFlow.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we’re always looking for passionate individuals ready to make an impact in the agricultural tech space.
We think you need these skills to ace Machine Learning Engineer - Robotics & Perception
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with machine learning pipelines, image segmentation, and any relevant projects that showcase your skills in robotics and perception.
Showcase Your Skills: Don’t just list your skills; demonstrate them! Include specific examples of how you've used frameworks like PyTorch or TensorFlow in your previous work. This will help us see your practical experience in action.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for your achievements and responsibilities to make it easy for us to read through your experience quickly.
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 regarding your application status.
How to prepare for a job interview at Jonathan Lee Recruitment
✨Know Your Tech Inside Out
Make sure you’re well-versed in the machine learning frameworks mentioned in the job description, like PyTorch and TensorFlow. Brush up on your knowledge of CNN architectures, especially YOLO, and be ready to discuss how you've applied these technologies in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in machine learning or computer vision engineering. Think about how you designed and optimised models for real-world applications, particularly in constrained environments. Real examples will make your experience stand out!
✨Collaborate Like a Pro
Since this role involves working with cross-functional teams, be ready to talk about your collaboration experiences. Highlight any projects where you worked closely with robotics or systems engineers, and how you integrated perception modules into broader system architectures.
✨Document Your Journey
Emphasise the importance of thorough documentation in your work. Be prepared to explain how you maintain records of model architectures, experiment results, and deployment procedures. This shows that you value quality and can contribute to the company’s commitment to continuous learning.