Computer Vision Engineer
Computer Vision Engineer

Computer Vision Engineer

Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
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Faculty

At a Glance

  • Tasks: Lead innovative AI projects in the defence sector, architecting cutting-edge computer vision systems.
  • Company: Join Faculty, a leader in responsible AI with a focus on real-world impact.
  • Benefits: Enjoy unlimited annual leave, private healthcare, and flexible working options.
  • Other info: Diverse and inclusive team culture with excellent career growth opportunities.
  • Why this job: Make a difference with state-of-the-art technology while shaping the future of AI.
  • Qualifications: Deep understanding of computer vision, strong Python skills, and leadership experience.

The predicted salary is between 60000 - 80000 £ per year.

We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI.

We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.

Our Defence team is focused on building and embedding human-centered AI solutions which give our nation a competitive edge in the defence sector. We collaborate with our clients to bring ethical, reliable and cutting-edge AI to high-stakes situations and maintain the balance of global powers essential to our liberty.

Because of the nature of the work we do with our Defence clients, you will need to be eligible for UK Security Clearance (SC) and willing to work between 2 to 4 days per week on-site with these customers which may require travel to locations throughout the UK. When not required on client sites, you’ll have the flexibility to work from our London office or remotely from elsewhere within the UK.

We are seeking a visionary Computer Vision (CV) Specialist to lead our most ambitious AI initiatives within the defence sector. Bridging the gap between cutting-edge research and real-world deployment, you will act as a primary technical authority, architecting sophisticated CV systems that solve critical customer challenges.

This is an entrepreneurial opportunity to shape our technical strategy, drive capability development, and represent the business unit as a thought leader. If you thrive on autonomy and want to push the boundaries of applying State-of-the-Art (SOTA) technology, this role offers the platform to make a definitive impact.

What you’ll be doing:

  • Delivering high impact, hands-on computer vision work and architecting technical solutions for complex project requirements.
  • Leading the technical delivery of CV projects and providing expert guidance to multidisciplinary teams throughout the development lifecycle.
  • Winning new business by contributing expert CV insight to bids and identifying opportunities to integrate advanced visual intelligence into customer solutions.
  • Staying at the forefront of the field by mastering SOTA developments and sharing best practices across the business unit to maintain a competitive edge.
  • Representing the organisation both internally and externally as an authoritative voice and subject matter expert in computer vision.
  • Partnering with leadership to define the technical strategy for CV work and taking ownership of capability development within the Defence domain.
  • Mentoring and developing talented team members who share an interest in CV, fostering an environment of continuous learning and technical excellence.

Who we’re looking for:

  • You possess a deep understanding of State-of-the-Art Computer Vision/AI approaches and feel confident applying both machine learning and classical computer vision techniques to real-world problems.
  • You are an experienced technical leader who enjoys the challenge of guiding teams and turning real world problems into architecting system architectures with minimal oversight.
  • You have a proven track record of deploying CV models into production environments and navigating the practicalities of real-world deployment, performance and latency.
  • You bring a collaborative and entrepreneurial mindset, with the ability to communicate technical concepts effectively to both specialist colleagues and non-technical clients.
  • Your background includes meaningful experience in Python, including object-oriented programming, and you are comfortable exploring low-level components when necessary.
  • You are passionate about capability building, whether through developing R&D accelerators or helping others sharpen their technical skills through mentorship.

The Interview Process:

  • Talent Team Screen (30 minutes)
  • Introduction to the team (30 minutes)
  • Technical Interview (90 minutes)
  • Commercial Interview (60 minutes)

Our Recruitment Ethos:

We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.

Some of our standout benefits:

  • Unlimited Annual Leave Policy
  • Private healthcare and dental
  • Enhanced parental leave
  • Family-Friendly Flexibility & Flexible working
  • Sanctus Coaching
  • Hybrid Working

If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don’t hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.

Computer Vision Engineer employer: Faculty

At Faculty, we pride ourselves on being at the forefront of AI innovation, offering a dynamic work environment that fosters intellectual curiosity and collaboration. Our commitment to employee growth is evident through our mentorship programmes and the opportunity to lead cutting-edge projects in the defence sector, all while enjoying benefits like unlimited annual leave and flexible working arrangements. Join us in London, where you can make a meaningful impact in a supportive culture that values diversity and encourages you to push the boundaries of technology.
Faculty

Contact Detail:

Faculty Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Computer Vision Engineer

✨Tip Number 1

Network like a pro! Reach out to people in the industry, attend meetups, and connect with Faculty employees on LinkedIn. Building relationships can open doors that applications alone can't.

✨Tip Number 2

Prepare for your interviews by brushing up on your technical skills and understanding the latest trends in computer vision. Show us you’re not just a candidate, but a thought leader ready to contribute to our innovative projects.

✨Tip Number 3

Don’t just wait for job postings! If you’re passionate about what we do at Faculty, reach out directly. Express your interest and share how your skills align with our mission in AI.

✨Tip Number 4

Be ready to showcase your past projects during interviews. We want to see how you've tackled real-world problems with your computer vision expertise. Bring your A-game and let your work speak for itself!

We think you need these skills to ace Computer Vision Engineer

Computer Vision
Machine Learning
Classical Computer Vision Techniques
Python
Object-Oriented Programming
Technical Leadership
System Architecture
Deployment of CV Models
Performance Optimisation
Collaboration
Communication Skills
Mentorship
Capability Development
State-of-the-Art (SOTA) Technology Mastery

Some tips for your application 🫡

Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Computer Vision Engineer role. Highlight your expertise in State-of-the-Art techniques and any relevant projects you've worked on, especially those that showcase your ability to solve real-world problems.

Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about AI and how you can contribute to our Defence team. Share specific examples of your past work in computer vision and how it relates to the challenges we face in the defence sector.

Showcase Your Technical Skills: Don’t shy away from detailing your technical prowess! Mention your experience with Python, machine learning, and any successful deployments of CV models. We want to see how you can bridge the gap between research and real-world applications.

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 this exciting opportunity. Plus, it shows us you’re keen to join our team!

How to prepare for a job interview at Faculty

✨Know Your CV Inside Out

Make sure you can discuss your previous projects and experiences in computer vision with confidence. Be ready to explain the technical challenges you faced, how you overcame them, and the impact of your work. This will show your depth of knowledge and practical experience.

✨Stay Updated on SOTA Developments

Familiarise yourself with the latest trends and advancements in computer vision and AI. Being able to discuss recent breakthroughs or tools during your interview will demonstrate your passion for the field and your commitment to staying at the forefront of technology.

✨Prepare for Technical Questions

Expect to face technical questions that assess your understanding of both machine learning and classical computer vision techniques. Brush up on key concepts, algorithms, and frameworks, and be prepared to solve problems on the spot to showcase your analytical skills.

✨Showcase Your Leadership Skills

Since the role involves leading teams and mentoring others, be ready to share examples of how you've guided teams in the past. Highlight your collaborative mindset and ability to communicate complex ideas clearly, as this will resonate well with the interviewers looking for a strong technical leader.

Computer Vision Engineer
Faculty
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