ExTrac AI
Machine Learning Engineer

How your CV stacks up
Upload your CV to see how well it fits this job role
?%
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
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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 energized 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


Get help with your application
Your very own career expert that helps elevate your application to the next level.
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.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Location