At a Glance
- Tasks: Design and train cutting-edge machine learning solutions for digital identities.
- Company: Join a dynamic team at a leading tech company focused on innovation.
- Benefits: Enjoy competitive salary, health benefits, and hybrid work flexibility.
- Other info: Collaborate with top scientists and enjoy excellent career growth opportunities.
- Why this job: Make a real impact in areas like deepfake detection and bias mitigation.
- Qualifications: Strong experience in machine learning, computer vision, and Python coding.
The predicted salary is between 50000 - 70000 £ per year.
We are looking for an Applied Scientist I to design and train cutting‑edge machine learning solutions related to digital identities. Work on challenging problems in deepfake detection, bias mitigation, document understanding, anomaly detection and/or efficient machine learning.
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.
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.
Location: London, hybrid: 3 days per week in office.
Applied Scientist I — Vision & Identity ML (Hybrid) employer: Dormont Manufacturing Co
Entrust is an exceptional employer that fosters a collaborative and innovative work culture, particularly for the Applied Scientist I role in London. With a strong emphasis on employee growth, you will have the opportunity to work with cutting-edge machine learning technologies while contributing to meaningful projects that impact digital identity solutions. The hybrid work model allows for flexibility, ensuring a balanced work-life experience, while the commitment to diversity and inclusion creates a welcoming environment for all employees.
StudySmarter Expert Advice🤫
We think this is how you could land Applied Scientist I — Vision & Identity ML (Hybrid)
✨Tip Number 1
Network like a pro! Reach out to current employees at the company through LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing a role in the Applied Scientist team.
✨Tip Number 2
Show off your skills! Prepare a portfolio of your projects related to machine learning and computer vision. Make sure to highlight any work on deepfake detection or bias mitigation, as these are hot topics in the field.
✨Tip Number 3
Get involved in the community! Attend conferences or webinars related to machine learning. This not only helps you learn but also gives you a chance to meet potential colleagues and showcase your passion for the field.
✨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, it shows you’re genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Applied Scientist I — Vision & Identity ML (Hybrid)
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 challenges we face, like deepfake detection and bias mitigation.
Showcase Your Projects:Include any relevant projects or research you've done, especially if you've published in top-level conferences. This helps us see your hands-on experience and passion for cutting-edge ML solutions.
Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you're excited about this role. Share your thoughts on the importance of fair ML products and how you can contribute to our team’s goals.
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 you’re interested in!
How to prepare for a job interview at Dormont Manufacturing Co
✨Know Your ML 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 apply it practically.
✨Showcase Your Projects
Prepare to talk about your past projects, particularly those involving Python and PyTorch. Highlight any high-performance ML-driven products you've delivered and be ready to discuss the challenges you faced and how you overcame them. Real-world examples will make you stand out!
✨Understand the Team's Goals
Research the company’s current projects and goals, especially around identity-focused products. Understanding their mission will help you align your answers with what they’re looking for, showing that you’re genuinely interested in contributing to their success.
✨Ask Smart Questions
Prepare insightful questions about the team dynamics, the tools they use (like AWS, Encord, etc.), and their approach to model deployment. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.
