At a Glance
- Tasks: Build innovative ML solutions for document verification and fraud prevention.
- Company: Join a dynamic tech company focused on cutting-edge document extraction.
- Benefits: Enjoy flexible work options, career growth opportunities, and a collaborative environment.
- Other info: Be part of a diverse team that values continuous improvement and collaboration.
- Why this job: Make a real impact in the world of document security and customer onboarding.
- Qualifications: Experience in ML systems, strong coding skills, and a passion for problem-solving.
The predicted salary is between 70000 - 90000 £ per year.
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
Senior ML Engineer, Doc Fraud employer: Entrust Corporation
Entrust is an exceptional employer, offering a dynamic work environment in London or Lisbon where innovation meets inclusivity. With a strong focus on employee growth and flexible working options, you will have the opportunity to contribute to impactful identity and security systems while collaborating with a supportive team that values diverse perspectives. Join us to influence architecture and technical direction in a high-performing culture that prioritises work-life balance and continuous learning.
