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 on innovative projects.
- Other info: Fast-paced environment with opportunities for career growth and technical leadership.
- Why this job: Make a real impact in the AI field while working with advanced technologies.
- Qualifications: Strong Python skills and experience with computer vision techniques required.
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
- 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
- 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 in London employer: IO Associates
Join a dynamic technology company in London that is at the forefront of innovation, transforming legacy systems into cutting-edge operational intelligence. With a strong emphasis on collaboration and mentorship, we offer a vibrant work culture that fosters professional growth and encourages engineers to push the boundaries of computer vision technology. Enjoy competitive salaries, a supportive environment, and the opportunity to work on impactful projects that shape the future of real-time applications.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer - Computer Vision in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your computer vision projects. Whether it's GitHub repos or a personal website, let your work speak for itself. This is your chance to shine and demonstrate what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail. We want to see how you think and approach real-world problems!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search. So, get those applications in and let’s make it happen!
We think you need these skills to ace Machine Learning Engineer - Computer Vision in London
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 computer vision, and explain how your background makes you a great addition to our team.
Showcase Your Projects:If you've worked on any cool projects related to object detection or 3D reconstruction, make sure to mention them! We love seeing practical applications of your skills, so include links or descriptions of your work.
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’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at IO Associates
✨Know Your Tech Inside Out
Make sure you brush up on modern computer vision techniques like object detection and 3D reconstruction. Be ready to discuss your hands-on experience with tools like PyTorch and OpenCV, as well as any projects where you've deployed models into production.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex problems in previous roles. Think about times when you had to optimise inference pipelines or integrate ML solutions into existing systems, and be ready to explain your thought process.
✨Collaborate Like a Pro
Since this role involves working closely with product and backend teams, be prepared to discuss your collaboration experiences. Highlight any instances where you contributed to architectural decisions or mentored other engineers, showcasing your teamwork skills.
✨Stay Current with Research
Familiarise yourself with the latest research in machine learning and computer vision. Be ready to discuss how you evaluate academic findings and translate them into practical applications, as this will demonstrate your commitment to staying at the forefront of the field.
