At a Glance
- Tasks: Design and train cutting-edge machine learning solutions for digital identities.
- Company: Join a dynamic team of machine learning scientists at a leading tech company.
- Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborate with product engineering to deploy innovative identity-focused products.
- Why this job: Make a real impact by tackling challenges in deepfake detection and bias mitigation.
- Qualifications: Strong experience in machine learning, computer vision, and coding skills in Python and PyTorch.
The predicted salary is between 45000 - 60000 £ 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) in London 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 access to cutting-edge tools and a supportive ML Ops team, employees are encouraged to push the boundaries of machine learning research while enjoying opportunities for professional growth and development. The hybrid work model promotes a healthy work-life balance, making it an ideal environment for those passionate about creating impactful technology solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Applied Scientist I — Vision & Identity ML (Hybrid) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working in machine learning and computer vision. Attend meetups or webinars, and don’t be shy about sliding into DMs on LinkedIn. 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 related to deepfake detection, bias mitigation, or any other relevant work. This is your chance to demonstrate your coding prowess in Python and PyTorch. Make sure to highlight any published research too!
✨Tip Number 3
Prepare for interviews by brushing up on your machine learning theory and practical applications. Be ready to discuss your experience with model training and optimisation. Practise explaining complex concepts in simple terms – it shows you really understand your stuff!
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in our mission. Tailor your application to highlight how your skills align with our goals in building fair and cutting-edge ML products. Let’s make an impact together!
We think you need these skills to ace Applied Scientist I — Vision & Identity ML (Hybrid) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your machine learning and computer vision expertise, and don’t forget to mention any relevant projects or publications!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about the role and how your background aligns with our mission at StudySmarter. Keep it concise but impactful!
Showcase Your Projects:If you've worked on any cool ML projects, especially in areas like deepfake detection or bias mitigation, make sure to include them. We love seeing practical applications of your skills!
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 from our team!
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 experience you have with large-scale models or datasets, and be ready to explain your role in optimising training processes. Real-world examples will make your skills stand out.
✨Understand the Team's Goals
Research the company’s products and how the Applied Scientist team contributes to them. Knowing how your work can impact their identity-focused products will demonstrate your enthusiasm and alignment with their mission. It’s all about showing you’re a good fit for the team!
✨Ask Smart Questions
Prepare insightful questions about the team’s current challenges, tools they use, or their approach to bias mitigation. This not only shows your interest but also your critical thinking skills. Plus, it gives you a chance to assess if this is the right environment for you.
