Applied Scientist I

Position Overview

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

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