At a Glance
- Tasks: Design and train cutting-edge machine learning solutions for digital identities.
- Company: Join a forward-thinking tech company focused on innovation and inclusivity.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with a commitment to diversity and accessibility.
- Why this job: Make a real impact in the exciting field of machine learning and digital identity.
- Qualifications: Strong background in machine learning, computer vision, and coding skills in Python.
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. 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 Recruiter Grace Rusingiza.
Applied Scientist I in London 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 in London
✨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 related to machine learning and computer vision. This is your chance to demonstrate your expertise in deepfake detection and bias mitigation—make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your coding skills in Python and PyTorch. Practice common ML problems and be ready to discuss your past projects and how they relate to the role of Applied Scientist I.
✨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 genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Applied Scientist I in London
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.
Show Off Your Coding Skills:Since coding is key for this role, consider including links to any GitHub repositories or projects that demonstrate your Python and PyTorch skills. 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. Plus, it’s super easy to do!
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 your experience with deepfake detection, bias mitigation, and other relevant topics. They’ll want to see that you can not only talk the talk but also walk the walk!
✨Show Off Your Coding Skills
Since coding in Python and PyTorch is crucial for this role, be prepared to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice coding challenges related to ML and computer vision beforehand.
✨Bring Your Research A-Game
If you've published any research, especially in top-level conferences, make sure to highlight it. Discussing your findings and how they relate to the role will show your passion and expertise in the field. It’s a great way to stand out!
✨Collaborate Like a Pro
This role involves working closely 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. Teamwork is key!
