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.

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.

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, Neutral 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

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

Pay: £70,000.00-£90,000.00 per year

Benefits:

• Company pension
• Private medical insurance
• Work from home

Work authorisation:

• United Kingdom (required)

Work Location: Hybrid remote in London SE1 8ND