Groundtruth AI
Senior Machine Learning Engineer

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Senior Machine Learning Engineer
About Groundtruth AI
Groundtruth AI was founded in 2024 to provide services and solutions for AI detection in Economic Crime Prevention for Financial Services. We focus on detection and prevention of Anti-Money Laundering and Terrorist Financing.
We exist to develop and deploy technologies that make a measurable difference in tackling financial crime. The billions of dollars stolen and laundered each year mask untold human suffering which we can help prevent.
We work with major tier 1 banks and major tech companies to deploy cutting-edge machine learning using some of the most exciting technology in the industry.
Your Role
We are looking for machine learning engineers to consult, build and deploy repeatable data and machine learning pipelines and AI solutions to our expanding portfolio of customers and into their cloud environments.
You’ll be involved and interested in the end-to-end delivery of systems. Exploring, understanding and processing data, designing and building pipelines, understanding model outputs and evaluating performance against defined objectives, and communicating these results. A proactive and driven approach to problem solving and solutionizing is key. You’ll also need good client facing skills and an ability to communicate complex technical ideas to varied audiences.
We are a small company, and you will have an opportunity to shape our solutions, direction and decision making. You will have a demonstrable track record of getting things done in environments where the objectives are sometimes ambiguous. You will be comfortable working with novel technologies and techniques as you go along, and owning a problem from end to end.
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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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.
Key Responsibilities
- End-to-End ML Pipeline Development: Design, train, tune, test, and deploy robust, repeatable ML model pipelines for financial crime detection.
- Data Analysis: Perform data analysis on large financial datasets to validate data integrity, design features, accommodate data quality issues and identify patterns for solutions.
- Production Deployment: Understand, advise and configure client infrastructure for pipeline execution within cloud environments.
- Customer Collaboration: Work with client business and engineering teams to understand their requirements, explain solutions and discuss results to maximum effect.
- Roadmap Contributions: Actively contribute to our technical and development roadmap and direction.
Experience
3+ years experience of the following are required:
- Developing Machine Learning pipelines and MLOps
- Data analysis, data exploration and identifying patterns
- Delivering software into large enterprise environments
- Developing or deploying models (Decision Trees, Neural Nets, etc), feature engineering, model evaluation and iteration
- Understanding of statistics, e.g. significance, confidence intervals
- Developing and debugging data transformations on large scale data platforms
- Working as part of a development team with version control technologies
- Client facing skills, or equivalent demonstration of stakeholder management
Experience with the following is highly desirable:
- Financial Crime Domain - e.g. AML, Fraud, Screening, Transaction Monitoring
- Designing practical system architecture
- Agentic or LLM deployment experience
- Training deep neural networks, complex learning


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Tech stack
Required:
- Proficiency with Python and SQL
- Familiarity with at least one cloud platform or an enterprise environment - GCP / AWS / Azure
- Proficiency with version control/CI/CD - Git
- Familiarity with at least one OLAP enterprise data warehouse and optimization techniques - Snowflake, Bigquery, Hive, Redshift, Databricks, Spark
We work with a range of technologies and languages, familiarity with some of the below is desirable. An ability and desire to pick up and develop new skills will be expected:
- Typescript, Bigquery, Apache Ibis, Hamilton, DBT, pytorch, tensorflow.
Our culture
We are an early stage, small company with an engineering led approach and a focus on delivering high quality software. We value attitude, collaboration, respect for others and taking proactive actions alongside engineering expertise.
You don’t need to be an AI expert in financial crime, but you do need the intellectual curiosity to learn.
Education
- First or Upper Second Bachelor’s degree in a numerate or relevant field (Maths, Physics, Computer Science, etc) or equivalent experience.
Language
- Fluent English
Benefits
- Hybrid Working - Minimum 2 days in the office in London. Additional office days may be expected during probation.
- £70k-£90k (depending on experience and seniority level)
- Workplace pension scheme
- Bonus up to 15% of base salary, dependent on personal and company performance
- Private medical insurance
- 25 days holiday
Job Type: Full-time
Benefits:
- Company pension
- Private medical insurance
- Work from home
Work authorisation:
- United Kingdom (required)
Work Location: Hybrid remote in London SE1 8ND
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