At a Glance
- Tasks: Lead a team in developing cutting-edge vision-language models and drive innovative projects.
- Company: Join a forward-thinking tech company committed to diversity and innovation.
- Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with opportunities to publish research and advance your career.
- Why this job: Make a real impact in the exciting field of machine learning and computer vision.
- Qualifications: Proven leadership in ML, strong coding skills, and a passion for innovation.
The predicted salary is between 80000 - 100000 £ per year.
Location: London, UK (Hybrid – 3 days in office)
Position Overview
You will lead a team of 6 applied scientists in training and evaluating vision‑language models for data extraction and tiny mobile models. The role is 50% hands‑on coding and 50% leadership.
Responsibilities
- Define the team’s roadmap in collaboration with product and engineering leads.
- Stay up‑to‑date on vision‑language and efficient ML literature, translating insights into product opportunities.
- Manage a team of 6 Applied Scientists.
- Contribute to dataset creation, model training, and evaluation code.
- Push research frontiers in vision‑language modeling, document understanding, few‑shot learning, distillation, quantization, and active learning.
- Publish research results in national and international conferences and scientific journals.
Qualifications
- 2+ years of experience leading a team of ML scientists or research engineers.
- 5+ years industry experience as an individual contributor in a machine learning science team.
- Strong experience in machine learning and computer vision.
- Strong record of delivering high‑performance ML‑driven products.
- Deep understanding of machine learning theory.
- Strong coding skills in Python and PyTorch.
Preferred Experience
- Technical experience in document understanding, vision‑language modeling, few‑shot learning, distillation, quantization, and active learning.
- Publications at top‑level machine learning conferences.
- Experience optimizing distributed training code.
Equal Opportunity Statement
Entrust is an EEO/AA/Disabled/Veteran Employer and is committed to building a diverse workforce. We welcome applications from qualified individuals of all backgrounds and strive to provide an accessible experience for candidates of all abilities.
Applied Science Manager – Computer Vision / ML in London employer: Entrust
Entrust is an exceptional employer that fosters a collaborative and innovative work culture, particularly for the Applied Science Manager role in London. With a strong emphasis on employee growth, you will have the opportunity to lead a talented team while engaging in cutting-edge research and development in machine learning and computer vision. The hybrid work model allows for flexibility, and the company's commitment to diversity ensures a welcoming environment for all employees.
StudySmarter Expert Advice🤫
We think this is how you could land Applied Science Manager – Computer Vision / ML in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the ML and computer vision space. Attend meetups, webinars, or conferences to meet potential employers and showcase your expertise.
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your projects in machine learning and computer vision. Share your GitHub repos or any publications you've contributed to – it’s a great way to impress hiring managers.
✨Tip Number 3
Prepare for interviews by brushing up on your coding skills and ML concepts. Practice common technical questions and be ready to discuss your past projects in detail. We want you to shine!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Applied Science Manager – Computer Vision / ML in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in machine learning and computer vision. We want to see how your skills align with the role, so don’t be shy about showcasing your leadership experience and technical expertise!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about applied science and how you can contribute to our team. We love seeing candidates who can connect their experiences to our mission.
Showcase Your Projects:If you've worked on relevant projects, whether in a professional or personal capacity, make sure to mention them. We’re interested in your hands-on coding experience and any innovative solutions you've developed in the field of ML.
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 to do!
How to prepare for a job interview at Entrust
✨Know Your Stuff
Make sure you brush up on the latest trends in computer vision and machine learning. Familiarise yourself with vision-language models, few-shot learning, and other key areas mentioned in the job description. Being able to discuss recent papers or breakthroughs will show your passion and expertise.
✨Showcase Your Leadership Skills
Since this role involves managing a team, be prepared to share examples of how you've successfully led projects or teams in the past. Highlight your experience in mentoring others and how you’ve contributed to their growth. This will demonstrate that you’re not just a tech whiz but also a great leader.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions during the interview. Brush up on your Python and PyTorch skills, and be ready to solve coding problems on the spot. Practising common ML algorithms and their applications can give you an edge.
✨Align with Their Vision
Research the company’s products and their roadmap. Be ready to discuss how your experience aligns with their goals and how you can contribute to their vision. Showing that you understand their mission and can translate insights into product opportunities will set you apart.