Entrust
Senior Applied Scientist - Computer Vision
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Senior Applied Scientist - Computer Vision
Senior Applied Scientist – Identity Portfolio • Entrust
Join Us at Entrust
At Entrust, we are shaping the future of identity-centric security solutions. From our comprehensive portfolio of solutions to our flexible, global workplace, we empower careers, foster collaboration, and build solutions that help keep the world moving safely.
Get to Know Us Headquartered in Minnesota, Entrust is an industry leader in identity-centric security solutions, serving over 150 countries with cutting-edge, scalable technologies. Our people make the difference—through curiosity, dedication, and innovation we drive success and anticipate the future.
About the Team:
You’ll be joining the team leading Entrust’s Identity portfolio (formerly Onfido, an AI-powered digital identity solution). Our technology helps businesses verify real identities using machine learning, enabling secure remote customer onboarding. By assessing government-issued identity documents and facial biometrics with state-of-the-art techniques, we empower companies to operate securely while ensuring seamless and safe access for customers.
Our Applied Scientist team consists of around twenty machine learning specialists, backed by an ML Ops team. This team provides advanced tooling using AWS, Encord, Ray, PyTorch Lightning, and Weights & Biases, enabling the Applied Science team to work closely with product engineering to deploy models globally.
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Position Overview
We are hiring a Senior Applied Scientist to develop and train cutting-edge machine learning solutions focused on digital identities. Join us in tackling critical challenges in areas like deepfake detection, bias mitigation, document understanding, anomaly detection, and efficient ML.
What You’ll Do
- Push the frontier of ML research in deepfake detection, bias mitigation, fraud/anomaly detection, face matching, document understanding, and efficient on-device ML.
- Publish research findings in national and international conferences and journals.
- Collaborate with product and engineering teams to enhance our world-class identity-focused solutions.
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.
- Develop a multi-modal document understanding model from scratch using synthetic data.
- Optimize LoRA adapter latency in PEFT/Triton deployments.
- Profile, debug, and improve model training speed across multiple GPUs.
- Create a large-scale dataset for deepfake detection.
- Test multimodal models for fraud detection experiments.
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What You’ll Need
You may be a great fit if you:
- Have strong experience in machine learning and computer vision.
- Successfully deliver high-performance ML-driven products.
- Possess a deep understanding of ML theory and its practical applications.
- Are proficient in Python and PyTorch with strong coding skills.
- Are passionate about building fair, cutting-edge ML solutions.
Preferred credentials: Technical expertise in:
- Face matching
- Bias mitigation
- Anomaly detection
- Document understanding
- On-device ML
Or related experience such as:
- Publication record in top-tier ML conferences.
- Experience optimising distributed training code.
Location
This role is based in our London, UK office with a hybrid working model (3 days per week in-office).
Ready for Impact?
Join us if you’re excited about pushing ML boundaries—solving problems, publishing research and making the world a safer place. Let’s build together.
Apply today!
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