Senior ML Engineer, Doc Fraud

Entrust Corporation; Greater London; Hybrid; GBP 90,000 - 140,000; Full time

Benefits offered by this job

Career Growth

Remote/Hybrid flexibility

Collaborative culture

Diversity & Inclusion

Job summary

Entrust is seeking a Senior ML Engineer to advance document extraction across our products, combining ML research with production systems. You will own end‑to‑end design, collaborate with data science and product teams, and optimize pipelines for global document coverage while supporting secure onboarding and fraud prevention initiatives.

The role is London‑hybrid with additional Portugal options, offering flexible remote/hybrid arrangements.

Qualifications

• Production engineering experience: built, deployed and operated complex systems with observability, reliability and performance optimisation.
• Hands-on LLM/ML systems experience: fine-tuning models, training/evaluation pipelines, latency/cost optimisation, productionising ML.
• Technical depth and breadth: T-shaped expertise in ML infrastructure or backend systems with broad software engineering knowledge.
• End‑to‑end ownership: lead projects from idea through design, implementation and production with minimal oversight.
• Tech stack: Python, Ruby, Typescript; running on AWS with Kubernetes.
• Strong judgement and initiative: make sound technical decisions in ambiguous situations; coordinate cross‑team solutions.
• Mentorship and collaboration: guide junior engineers and review code, promote team spirit.

Responsibilities

• Collaborate with Applied Science, Product, Design, Data Science and Operations to deliver accurate document classification and extraction across thousands of documents globally.
• Lead the technical design of complex features and systems from RFC through production deployment.
• Build and optimise production ML systems: training/evaluation/deployment pipelines; GPU inference optimisations; robust labeling workflows.
• Ensure performance, scalability and reliability by understanding production systems and addressing technical debt.
• Drive technical excellence: RFCs, code reviews, documentation, and trade-off decisions across priorities.
• Coordinate solutions across teams and align with Product to deliver on commitments.
• Mentor engineers through pair programming and guidance; foster collaboration and problem-solving.
• Contribute to a culture of continuous improvement and psychological safety.

Skills

Python

Ruby

Typescript

LLM systems

AWS

Tools

TensorFlow

PyTorch

Triton

Kubernetes

Job description

Senior ML Engineer – Document Extraction

Locations: London (Hybrid, 3 days onsite), Portugal (Hybrid or Remote)

Department: Engineering
Reports to: Engineering Manager
Job Type: Full-Time

Job Summary

We’re looking for a Senior Software Engineer to join our Document Fraud team, where you’ll build products that delight customers across all our product offerings including financial services, driving verification, proof of address, and much more. Your focus will be on delivering high‑accuracy extraction with global document coverage, contributing to our Document Verification offering and enabling secure document verification, fraud prevention, and seamless customer onboarding experiences.

Responsibilities

• Work closely with Applied Science, Product, Design, Data Science, and Operations to deliver highly accurate and performant document classification and extraction solutions across thousands of documents globally.
• Lead the technical design of complex features and systems, taking ownership from RFC through implementation to production deployment.
• Build and optimise production ML systems: develop repeatable pipelines for training, evaluating, and deploying LLM models; implement GPU optimisations for inference; design advanced labeling workflows to improve model accuracy; and engineer robust solutions that deliver measurable customer value.
• Champion performance, scalability, and reliability by deeply understanding how our systems operate in production and by identifying and tackling technical debt proactively.
• Drive technical excellence across the team by leading RFCs, reviewing critical code, holding peers accountable for quality (code review, testing, documentation), and making well‑reasoned trade‑offs between competing priorities.
• Work with Product to prioritise features and ensure the team delivers on its commitments.
• Mentor and enable other engineers through pair programming, technical guidance, and collaborative problem‑solving.
• Coordinate solutions to cross‑cutting technical problems, working seamlessly across team and organisational boundaries.
• Contribute to a culture of continuous improvement, psychological safety, and collaboration through active participation in our squad‑based organisation, retrospectives, written documentation (RFCs, DACIs), and cross‑functional partnerships.

Qualifications

• Strong production engineering experience: built, deployed and operated complex systems in production with observability, reliability, performance optimisation and operational realities.
• Hands‑on LLM/ML systems experience: fine‑tuning models, building inference pipelines, optimisation for latency/cost, evaluation of model performance; comfortable with TensorFlow, PyTorch, Triton and productionising ML.
• Technical depth and breadth: T‑shaped expertise in at least one area (ML infrastructure, backend systems, performance optimisation) with broad understanding across software engineering.
• End‑to‑end ownership: take complex projects from idea through design, implementation and production with minimal oversight.
• Tech stack: Python, Ruby, Typescript; running on AWS with Kubernetes.
• Strong judgement and initiative: make sound technical decisions in ambiguous situations; take initiative across multiple areas and coordinate cross‑team solutions.
• Mentorship and collaboration: guide junior engineers, provide constructive code reviews, adapt communication style, promote team spirit.
• Pragmatic problem‑solving: identify technical debt, tackle it strategically; seek empirical evidence; balance short‑term needs with long‑term architecture.

Benefits

• Career Growth: learning‑forward initiatives and exciting challenges to support your professional journey.
• Flexibility: remote, hybrid or on‑site options that fit your lifestyle.
• Collaboration: teamwork that thrives on sharing ideas, brainstorming solutions, and building a better tomorrow.
• Diversity & Inclusion: a culture built on diversity, inclusion and respect with global affinity groups and unconscious bias training.

EEO Statement

Entrust is an EEO/AA/Disabled/Veterans Employer. Entrust values diversity and inclusion and we are committed to building a diverse workforce with wide perspectives and innovative ideas. We welcome applications from qualified individuals of all backgrounds and strive to provide an accessible experience for candidates of all abilities. If you require an accommodation, contact [e-mail].