At a Glance
- Tasks: Design and train innovative machine learning solutions for digital identities.
- Company: Join Entrust, a leader in AI-powered digital identity solutions.
- Benefits: Enjoy 25 days leave, private medical insurance, and a life enrichment allowance.
- Other info: Hybrid work model with vibrant team culture and growth opportunities.
- Why this job: Work on impactful projects like deepfake detection and bias mitigation.
- Qualifications: Strong experience in machine learning, Python, and PyTorch required.
The predicted salary is between 60000 - 80000 ÂŁ per year.
About the Team:
You'll be joining the team leading Entrust's Identity portfolio, formerly known as Onfido (an AI-powered digital identity solution). Our technology helps businesses verify real identities using machine learning, ensuring secure remote customer onboarding. By assessing government-issued identity documents and facial biometrics using state-of-the-art machine learning, we provide companies with the assurance they need to operate securely while allowing people to access services quickly and safely.
Our Applied Scientist team consists of about twenty machine learning scientists. The team is supported by an ML Ops team that provides state-of-the-art tooling (including AWS, Encord, Ray, PyTorch Lightning and Weights & Biases). The Applied Science team works closely with product engineering to deploy models to serve our worldwide customer base.
Position Overview:
We are looking for an Applied Scientist II to design and train cutting-edge machine learning solutions related to digital identities. Join our team and work on challenging problems in deepfake detection, bias mitigation, document understanding, anomaly detection and/or efficient ML.
What you will be doing:
- Push the frontier of research in areas such as deepfake detection, bias mitigation, fraud/anomaly detection, face matching, document understanding, and efficient on-device ML.
- Publish research results in national and international conferences and scientific journals.
- Work with product and engineering to improve our world-class identity-focused products.
Representative work:
- Implement bias-mitigation strategies to build fair face-matching and deepfake-detection models.
- Train and benchmark large-scale vision-language models for document extraction.
- Train a multi-modal document understanding model from scratch using synthetic data.
- Optimise LoRA adapter latency in PEFT/Triton.
- Profile, debug and improve model training speed on multiple GPUs.
- Create a large-scale dataset for deepfake detection.
- Experiment with multimodal models to detect fraud.
You may be a good fit if you:
- Have strong experience in machine learning and computer vision.
- Have a strong record of successfully delivering high-performance ML-driven products.
- Have a deep understanding of machine learning theory.
- Have strong coding skills in Python and PyTorch.
- Care about building fair and cutting-edge machine learning products.
Strong candidates may also have:
- Technical experience in one or more of the following areas: face matching, bias mitigation, anomaly detection, document understanding or on-device ML.
- Published at top-level machine learning conferences.
- Experience optimising (distributed) training code.
Where you will be:
This role is based in our London, UK office and follows a hybrid model, requiring in-office presence three days per week.
Benefits UK:
- 25 days annual leave plus a day off for your Birthday.
- Two paid volunteering days per year.
- Bupa Private Medical and Dental Insurance.
- Pension with The People’s Pension (employer contribution 4% of base salary).
- Generous paid parental leave.
- Life enrichment allowance of up to ÂŁ80 per month to use for services including gym, yoga, fitness classes, massages, childcare, and therapy.
- Dedicated learning opportunities including using tools like Linkedin Learning with availability to use for learning resources such as books, coaches, conferences, courses, podcasts, and more.
- Our open and transparent culture is reflected in our “Better Together” motto and we bring this to life by meeting once a week for our global weekly roundup (OnThursday); holding quarterly team socials, and other company-wide social events.
- Expense up to ÂŁ300 (or local equivalent) to purchase workstation setup equipment.
- The opportunity to become a member of Entrust’s resource groups in order to learn different skills in our belonging groups.
Ready to Make an Impact?
If you’re excited by the prospect of working on cutting-edge machine learning for problems that matter, Entrust is the place for you. Join us in making a difference. Let’s build a more secure world—together. Apply today!
Research Scientist in Science in London employer: Entrust
Contact Detail:
Entrust Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Scientist in Science in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and computer vision. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common ML-related questions and be ready to discuss your past projects in detail.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Research Scientist in Science in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the role of Research Scientist. Highlight your machine learning projects, especially those related to deepfake detection or bias mitigation, as these are key areas for us.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about machine learning and how your background makes you a great fit for our team. Share specific examples of your work that demonstrate your expertise in computer vision and ML-driven products.
Showcase Your Research: If you've published any research, make sure to mention it! We love seeing candidates who have contributed to top-level conferences. This shows us your commitment to pushing the boundaries in machine learning.
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 Entrust
✨Know Your Machine Learning Stuff
Make sure you brush up on your machine learning and computer vision knowledge. Be ready to discuss specific algorithms, models, and techniques you've worked with, especially in areas like deepfake detection and bias mitigation. This will show that you're not just familiar with the theory but can also apply it practically.
✨Showcase Your Coding Skills
Since strong coding skills in Python and PyTorch are essential, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot or discuss your previous projects. Bring examples of your work or even a portfolio if you have one!
✨Understand Their Products
Familiarise yourself with Entrust's identity solutions and how they leverage machine learning. Being able to discuss how your skills can directly contribute to improving their products will set you apart. Think about how you can push the frontier in areas like document understanding or anomaly detection.
✨Prepare Questions
Interviews are a two-way street! Prepare thoughtful questions about the team dynamics, ongoing projects, and the company culture. This shows your genuine interest in the role and helps you assess if it's the right fit for you. Plus, it gives you a chance to engage with your interviewers.