At a Glance
- Tasks: Develop and optimise cutting-edge computer vision models for real-time applications.
- Company: Join a dynamic tech company transforming sensor systems into operational intelligence.
- Benefits: Competitive salary, mentorship opportunities, and a chance to work with innovative technologies.
- Other info: Fast-paced environment with excellent growth potential and collaborative culture.
- Why this job: Make a real impact by deploying advanced ML solutions in exciting environments.
- Qualifications: Strong Python skills and experience with modern computer vision techniques required.
The predicted salary is between 80000 - 130000 £ per year.
We are seeking a Machine Learning Engineer to join a growing technology company focused on transforming legacy sensor systems into real-time operational intelligence. This role will play a key part in developing advanced computer vision capabilities including scene understanding, object detection, tracking, and 3D reconstruction from edge-deployed sensors. You will work closely with product and backend engineering teams to evaluate state-of-the-art research, build efficient inference pipelines, and deploy production-grade computer vision models into real-world environments.
Key Responsibilities
- Develop and optimise computer vision models for real-time applications
- Build capabilities across object detection, tracking, depth estimation, scene understanding, and 3D reconstruction
- Evaluate and benchmark state-of-the-art research models for production use
- Design and maintain scalable inference pipelines for edge-deployed systems
- Collaborate with backend and product teams to integrate ML solutions into production platforms
- Contribute to architectural decisions and technical direction within the ML/CV stack
- Support deployment and optimisation workflows for production inference systems
- Mentor engineers and contribute to engineering best practices within the team
Skills & Experience
- Strong understanding of modern computer vision techniques including object detection, tracking, SLAM, depth estimation, and 3D geometry
- Experience deploying machine learning and computer vision models into production environments
- Strong Python engineering skills
- Hands-on experience with PyTorch, Torchvision, OpenCV, and related ML tooling
- Experience optimising inference pipelines and working with deployment frameworks such as ONNX or TensorRT
- Ability to evaluate academic research and translate findings into practical product capabilities
- Strong architectural and problem-solving skills with the ability to work autonomously
- Comfort operating in fast-moving environments with evolving technical requirements
- Must be eligible for SC clearance
Desirable
- Experience working with edge-deployed sensor systems or real-time video processing
- Knowledge of efficient GPU inference and model optimisation techniques
- Experience leading technical initiatives or mentoring engineers
- Familiarity with experiment tracking and ML tooling such as PyTorch Lightning or Weights & Biases
- Experience building privacy-focused or security-focused AI systems
Machine Learning Engineer - Computer Vision employer: IO Associates
Join a forward-thinking technology company in London that is dedicated to innovation and excellence in machine learning and computer vision. With a strong emphasis on employee growth, you will have the opportunity to work alongside talented professionals, contribute to cutting-edge projects, and enjoy a collaborative work culture that values creativity and technical expertise. The company offers competitive salaries, mentorship opportunities, and a dynamic environment where your contributions directly impact the future of operational intelligence.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer - Computer Vision
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can land you that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to computer vision. We love seeing real-world applications of your work, so make sure to highlight any models you've deployed or optimised.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and ML concepts. We recommend doing mock interviews with friends or using platforms that focus on coding challenges. The more you practice, the more confident you'll feel!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for passionate candidates who are eager to dive into the world of machine learning and computer vision.
We think you need these skills to ace Machine Learning Engineer - Computer Vision
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with computer vision techniques and relevant projects. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you’re the perfect fit for this role. Share your passion for machine learning and how you’ve tackled challenges in previous projects. Keep it engaging and personal!
Showcase Your Technical Skills:When listing your skills, focus on those that are most relevant to the job description, like Python, PyTorch, and OpenCV. We love seeing hands-on experience, so mention any specific projects or models you've worked on.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re genuinely interested in joining our team!
How to prepare for a job interview at IO Associates
✨Know Your Computer Vision Stuff
Make sure you brush up on the latest computer vision techniques like object detection, tracking, and 3D reconstruction. Be ready to discuss how you've applied these in real-world scenarios, especially if you've worked with edge-deployed systems.
✨Show Off Your Python Skills
Since strong Python engineering skills are a must, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice writing clean, efficient code using libraries like PyTorch and OpenCV.
✨Talk About Your Deployment Experience
Be ready to share specific examples of how you've deployed machine learning models into production. Discuss any challenges you faced and how you optimised inference pipelines, especially with tools like ONNX or TensorRT.
✨Collaboration is Key
This role involves working closely with product and backend teams, so highlight your teamwork skills. Share experiences where you collaborated on projects, contributed to architectural decisions, or mentored others in best practices.
