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 a focus on research and development.
- 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. For accommodations, contact accessibility@entrust.com.
Applied Science Manager – Computer Vision / ML 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
✨Tip Number 1
Network like a pro! Reach out to your connections in the ML and computer vision space. Attend meetups, webinars, or conferences where you can chat with industry folks. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to vision-language models or any relevant ML work. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your coding skills in Python and PyTorch. Practice common ML problems and be ready to discuss your past projects. We want to see how you think and solve problems, so be confident and articulate!
✨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 that application in and let’s make some magic happen!
We think you need these skills to ace Applied Science Manager – Computer Vision / ML
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 leading a team in applied science. Share specific examples of your past successes and how they relate to the responsibilities outlined in the job description.
Showcase Your Projects:If you've worked on relevant projects, make sure to mention them! Whether it's dataset creation or model training, we love seeing real-world applications of your skills. Include links to any publications or code repositories if possible.
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 don’t miss out on any important updates. Plus, it shows you’re keen on joining our team!
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 recent papers and breakthroughs, especially in vision-language models. This will not only show your passion but also help you engage in meaningful discussions during the interview.
✨Showcase Your Leadership Skills
Since this role involves managing a team, be prepared to discuss your leadership style and experiences. Think of specific examples where you've successfully led a project or mentored team members. Highlight how you foster collaboration and innovation within your team.
✨Demonstrate Your Coding Proficiency
As the role is 50% hands-on coding, be ready to talk about your coding experience, particularly in Python and PyTorch. You might even be asked to solve a coding problem or discuss your approach to model training and evaluation, so practice articulating your thought process clearly.
✨Prepare Questions for Them
Interviews are a two-way street! Prepare insightful questions about the team's roadmap, current projects, and how they measure success. This shows your genuine interest in the role and helps you assess if the company aligns with your career goals.
