ExTrac AI
Machine Learning Engineer

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About ExTrac
ExTrac is a decision intelligence company used by public and private sector organisations 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.
About the Role
We are currently only able to consider applicants who are nationals of a NATO member state, Australia, or New Zealand.
This role is open at both mid and senior level. Scope, autonomy, and expected impact will scale with experience and ability. Senior candidates will typically lead technical direction on major initiatives, set standards across the team, and mentor others; mid-level candidates will own significant components end-to-end and contribute to broader technical decisions.
The Machine Learning team owns ExTrac’s modelling capabilities end-to-end. You will partner directly with software engineering and product design to understand requirements, design and run model evaluations, integrate optimised workflows into production pipelines, and ensure results remain reliable at scale.
You will architect cutting-edge agentic systems for large-scale analysis of the geopolitical landscape, train and evaluate domain-specific models for the unique problems our customers face, and work with design and engineering to bring them into the product. Alongside domain experts, you will translate research into practical solutions for analysts operating at the frontier of their field.
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.
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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.
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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.
In this role, you will set high technical standards and take projects from prototype to reliable production deployment. You will collaborate closely with the engineers who design the data collection and processing backend and engage directly with senior stakeholders.
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 you’ll do
- Design systems that balance research velocity with real product and production constraints
- Make (and help shape) technical decisions on model selection, training approaches, evaluation, and deployment
- Deliver production-ready systems at scale, combining research rigour with pragmatic engineering
- Take projects from early exploration through to reliable deployment
- Uphold high standards for architecture, code quality, evaluation, and research practice
What we’re looking for
- Technical excellence (working on production systems at scale, research that was used, or end-to-end ownership in an early-stage role)
- Hands-on experience with model serving (small models and LLMs), agent orchestration, and retrieval systems
- Rigour in evaluation and benchmarking
- Strong engineering fundamentals: ability to write clean, maintainable code, and design robust systems
- Comfort with a fast-paced environment and clear ownership
- Experience with modern coding agents and thoughtful views on effective workflows
What sets you apart
- Early-stage start-up experience
- Building agentic tools and harnesses
- Working on domain-specific modelling problems
- Clear writing, systematic thinking, and strong communication


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Interview Process
- Initial Intro Interview - 30 Minutes
- Technical Assessment - 1 hour
- System Design Assessment - 1 hour
- 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. The team is typically in our central London office two days a week, and you are welcome to come in up to five.
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.
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