At a Glance
- Tasks: Design and train cutting-edge machine learning solutions for digital identities.
- Company: Join a dynamic team of innovative machine learning scientists in London.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on diversity and inclusion.
- Why this job: Make a real impact by tackling challenges like deepfake detection and bias mitigation.
- Qualifications: Strong experience in machine learning, coding skills in Python and PyTorch.
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 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 global digital identities. The hybrid work model allows for flexibility, ensuring a healthy work-life balance, 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
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or at events. Ask them about their experiences and the team culture. This can give you insider info and might even lead to a referral!
✨Tip Number 2
Prepare for those interviews! Brush up on your machine learning concepts, especially around deepfake detection and bias mitigation. Practise explaining your past projects and how they relate to the role.
✨Tip Number 3
Show off your passion! When you get the chance, talk about your interest in building fair and cutting-edge ML products. Share any personal projects or research you've done that aligns with the company's goals.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Applied Scientist I
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 building 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 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 shows you're not just familiar with the theory but can 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 or explain your code from past projects. Practising coding challenges related to ML can really help you shine.
✨Talk About Your Research
If you've published research or presented at conferences, be ready to discuss your findings. Highlight how your work contributes to the field and how it relates to the company's goals. This not only shows your expertise but also your passion for advancing machine learning.
✨Understand the Company’s Products
Familiarise yourself with the company’s identity-focused products and think about how your skills can enhance them. Prepare some ideas on how you could contribute to improving their offerings, especially in areas like document understanding and anomaly detection. This will demonstrate your proactive approach and genuine interest in the role.
