About ExTrac

ExTrac is a decision intelligence company used by governments, defence organisations, financial institutions, and corporates operating in complex, fast-moving environments. Our capabilities fuse curated data sources, domain-specific AI, and deep human expertise to transform information overload into clear, actionable foresight.

Our ambition is to become the analytical backbone that organisations rely on when geopolitical uncertainty becomes an opportunity or a strategic risk. More at extrac.ai.

The Role

Location: Hybrid (In-office in London, minimum 2 days per week)

We are looking for an ML Engineer to join ExTrac's Machine Learning team, which owns our modelling capabilities end to end.

You will work with software engineering and product design to understand requirements, contribute to agentic systems for large-scale analysis of the geopolitical landscape, and help train and evaluate domain-specific models for the problems our customers face. Alongside domain experts, you will help translate research into practical solutions for analysts operating at the frontier of their field.

In this role, you will own well-defined components end-to-end and collaborate on broader technical decisions, working alongside senior engineers, with support on the more ambiguous or open-ended parts of a problem. You will take projects from prototype through to reliable production deployment.

We look for people who enjoy challenging problems, keep learning and build systems that scale. We value low ego, genuine ownership and a passion for applying AI to high-stakes intelligence challenges.

What the job involves

Contribute to designing systems that balance research velocity with product and production constraints
Help shape technical decisions on model selection, training approaches, evaluation and deployment for well-defined components
Build and ship production-ready components, combining research rigour with pragmatic engineering
Take projects from early exploration through to reliable deployment
Apply high standards for architecture, code quality, evaluation and research practices

You should apply if

You like using machine learning to solve challenging problems in a complex domain
You enjoy working closely with product, design and the analysts who use what you build, translating their feedback into technical decisions
You're energised by hands-on work with model serving (small models and LLMs), agent orchestration and retrieval systems
You care about engineering fundamentals: writing code that's clean and maintainable, not just code that works
You are comfortable with a fast-paced environment and clear ownership

Where this role can take you

This role positions you at the frontier of applied AI for high-stakes decision-making, giving you the chance to help shape production agentic systems that influence real geopolitical and organisational outcomes.
Depending on your interests, this role can open paths into specialised domain AI, technical leadership and lasting impact in the decision-intelligence space.

Requirements

Due to the nature of our work and the clients we support, applicants must be eligible to obtain UK security clearance. We are currently only able to consider applicants who are nationals of a NATO member state, Australia, or New Zealand.

2+ years of professional software engineering experience, with experience owning well-defined features or components end-to-end within a larger system
Technical excellence (contributing to production systems, research that was used, or hands-on ownership of well-defined components in an early-stage role)
Some hands-on experience with model serving (small models and LLMs), agent orchestration or retrieval systems
Developing rigour in evaluation and benchmarking, with support from senior engineers
Strong engineering fundamentals: ability to write clean, maintainable code
Comfort with a fast-paced environment and clear ownership of well-defined work
Exposure to modern coding agents and interest in effective workflows

Desirable

Early-stage start-up experience
Building agentic tools and harnesses
Working on domain-specific modelling problems
Clear writing, systematic thinking and strong communication

Interview Process

Initial Intro Interview - 30 Minutes
Technical Assessment - 45 minutes
System Design Assessment - 45 minutes
Founder interview - 30 Minutes

Benefits

Competitive salary based on skills and experience.
A generous benefits package, including Private Medical Health Insurance and enhanced pension contributions.
Enhanced parental leave and a workplace nursery scheme.
£500/year education budget with more expensive items (like conferences) covered with manager approval.
33 days of leave across the year inclusive of bank holidays.
Flexible working, hybrid: minimum 2 days per week in our central London office.

ExTrac AI provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, colour, religion, sex, national origin, age, disability, genetic information, sexual orientation, gender identity, or gender expression. We are committed to a diverse and inclusive workforce and welcome people from all backgrounds, experiences, perspectives, and abilities.

ExTrac AI is committed to a fair and transparent hiring process. We confirm that this advertisement is for an active, existing open role within our organisation. Please be advised that we may use artificial intelligence-driven tools to assist our recruitment team in screening, assessing, and selecting candidates for this position but all hiring decisions will be made by a member of our team.

Machine Learning Engineer