At a Glance
- Tasks: Design and train cutting-edge machine learning solutions for digital identities.
- Company: Join a forward-thinking tech company focused on identity solutions.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with chances to publish research and innovate.
- Why this job: Make a real impact in AI by tackling deepfake detection and bias mitigation.
- Qualifications: Strong background in machine learning, coding skills in Python and PyTorch.
The predicted salary is between 60000 - 80000 £ per year.
We are looking for an Applied Scientist I to design and train cutting-edge machine learning solutions related to digital identities. The role focuses on deepfake detection, bias mitigation, document understanding, anomaly detection, and efficient on-device ML.
What you will be doing:
- Push the frontier of research in 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.
- Collaborate with product and engineering teams to improve our world-class identity-focused products.
Representative work:
- Implement bias-mitigation strategies for fair face-matching and deepfake-detection models.
- Train and benchmark large-scale vision-language models for document extraction.
- Build a multi-modal document-understanding model from scratch using synthetic data.
- Optimize 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.
Qualifications:
- Strong experience in machine learning and computer vision.
- Proven record of delivering high-performance ML-driven products.
- Deep understanding of machine learning theory.
- Excellent coding skills in Python and PyTorch.
- Passion for building fair and cutting-edge machine learning products.
Additional preferences:
- Technical experience in face matching, bias mitigation, anomaly detection, document understanding, or on-device ML.
- Publications at top-level machine learning conferences.
- Experience optimizing (distributed) training code.
Location: London, hybrid: 3 days per week in office.
EEO Statement: Entrust is an EEO/AA/Disabled/Veterans Employer. We welcome applications from qualified individuals of all backgrounds and are committed to providing an accessible experience for candidates of all abilities. If you require an accommodation, contact accessibility@entrust.com.
Applied Scientist I employer: Entrust Corporation
Entrust is an exceptional employer that fosters a collaborative and innovative work culture, particularly for the role of Applied Scientist I in London. With a strong emphasis on employee growth, you will have the opportunity to push the boundaries of machine learning research while working alongside talented professionals in a hybrid environment that promotes work-life balance. The company values diversity and inclusion, ensuring that all employees can thrive and contribute meaningfully to cutting-edge projects in digital identity solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Applied Scientist I
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to deepfake detection or bias mitigation. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your machine learning theory and coding skills. Practice common interview questions and be ready to discuss your past projects in detail. Confidence is key!
✨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.
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 role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about deepfake detection and bias mitigation. Let us know what excites you about the role and how you can contribute to our team.
Showcase Your Coding Skills:Since excellent coding skills in Python and PyTorch are key for this role, consider including links to any relevant GitHub repositories or projects. We love seeing practical examples of your work!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the position. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Entrust Corporation
✨Know Your ML Stuff
Make sure you brush up on your machine learning and computer vision knowledge. Be ready to discuss deepfake detection, bias mitigation, and anomaly detection in detail. They’ll want to see that you can not only talk the talk but also walk the walk when it comes to implementing these concepts.
✨Show Off Your Coding Skills
Since coding is a big part of this role, be prepared to demonstrate your Python and PyTorch skills. You might be asked to solve a problem on the spot, so practice coding challenges related to ML. It’s all about showing them you can deliver high-performance ML-driven products.
✨Research and Publish
If you have any publications, make sure to highlight them during the interview. Discussing your research and how it relates to their work will show your passion for the field and your commitment to pushing the boundaries of machine learning.
✨Collaborate Like a Pro
This role involves working with product and engineering teams, so be ready to talk about your collaboration experiences. Share examples of how you’ve worked with others to improve products or solve complex problems. They’ll want to see that you can communicate effectively and contribute to a team environment.
