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- Tasks: Design and deploy computer vision models for immersive experiences in cultural spaces.
- Company: Join a dynamic AI startup revolutionising visitor interactions in museums and heritage sites.
- Benefits: Enjoy remote work flexibility and a competitive salary of £65k to £70k.
- Why this job: Lead AI innovation while collaborating with the founder on impactful tech solutions.
- Qualifications: Strong Python skills and experience with PyTorch or TensorFlow required.
- Other info: Flexible start date in July 2025; ideal for those passionate about AI and real-world applications.
The predicted salary is between 55000 - 70000 £ per year.
We’re partnered with a fast-growing early-stage startup that’s transforming how people experience real-world spaces like museums, aquariums, and heritage sites using AI, computer vision, and generative tech. They’ve nailed pilots with major cultural institutions and just closed their pre-seed round. Now they’re on the hunt for a Machine Learning Engineer to take full ownership of their AI stack and drive the next wave of innovation.
What You’ll Be Doing
- Designing, training, and deploying computer vision models to recognize exhibits and physical objects across large venues
- Integrating LLMs and retrieval-augmented generation (RAG) systems to enable contextual, safe, and engaging visitor conversations
- Developing voice interfaces using speech-to-text and text-to-speech for seamless hands-free experiences
- Building scalable infrastructure, backend APIs, and MLOps pipelines (preferably on AWS)
- Working closely with the founder to influence product roadmap and AI strategy
What They’re Looking For
- Strong Python skills with experience in PyTorch or TensorFlow frameworks
- Proven computer vision expertise or solid transferable ML experience
- Familiarity with cloud platforms and backend development focused on MLOps
- Experience or strong interest in LLMs, prompt engineering, AR, indoor navigation, or data infrastructure is a bonus
Why This Role?
- Lead and own the AI function from the ground up
- Work at the intersection of cutting-edge tech and real-world impact
- Collaborate directly with the founder and shape product and technology decisions
Interested? We’re already speaking with top ML and computer vision engineers. If you want to take on this challenge, let’s chat.
Computer Vision Engineer employer: LinkedIn
Contact Detail:
LinkedIn Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Computer Vision Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in computer vision and machine learning. Follow relevant blogs, attend webinars, and engage with communities on platforms like GitHub or LinkedIn to stay updated and showcase your passion during discussions.
✨Tip Number 2
Build a portfolio of projects that demonstrate your skills in Python, PyTorch, or TensorFlow. Having tangible examples of your work can set you apart and provide talking points during interviews.
✨Tip Number 3
Network with professionals in the AI and computer vision space. Attend industry meetups or conferences, and don’t hesitate to reach out to people on LinkedIn for informational chats. This can lead to valuable insights and potential referrals.
✨Tip Number 4
Prepare to discuss how you would approach integrating LLMs and RAG systems into existing frameworks. Being able to articulate your thought process and ideas will show your readiness to take ownership of the AI stack.
We think you need these skills to ace Computer Vision Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your strong Python skills and experience with PyTorch or TensorFlow. Include specific projects or roles where you've worked on computer vision or machine learning to demonstrate your expertise.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and how you can contribute to transforming real-world spaces. Mention any relevant experience with cloud platforms, MLOps, or LLMs, and explain why you're excited about this startup's mission.
Showcase Relevant Projects: If you have worked on projects related to computer vision, voice interfaces, or backend development, be sure to include these in your application. Provide links to your GitHub or portfolio to give them a clear view of your capabilities.
Follow Up: After submitting your application, consider sending a polite follow-up email after a week or two. This shows your enthusiasm for the role and keeps you on their radar as they review candidates.
How to prepare for a job interview at LinkedIn
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, PyTorch, and TensorFlow in detail. Bring examples of projects where you've designed or deployed computer vision models, as this will demonstrate your hands-on expertise.
✨Understand the Company’s Vision
Research the startup's mission and recent projects, especially their work with cultural institutions. This will help you align your answers with their goals and show that you're genuinely interested in contributing to their innovative approach.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving skills in machine learning and computer vision. Practice explaining your thought process clearly, as this will highlight your analytical abilities and how you approach challenges.
✨Demonstrate Collaboration Skills
Since you'll be working closely with the founder, emphasise your teamwork and communication skills. Share examples of how you've successfully collaborated on projects, particularly in fast-paced or startup environments.
