Senior Machine Learning Engineer
About Groundtruth AI
Groundtruth AI was founded in 2024 are just about to celebrate our first year. We are a Google Cloud partner working to help major financial institutions transform the way they find and fight financial crime. Our founders have worked with Google for years and were key figures in shaping and building Google’s latest Cloud product targeting Anti-Money Laundering. We exist to 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.
Our founders have worked with Google for years, and Groundtruth is a Google Cloud Platform partner working to help major financial institutions transform the way they find and fight financial crime. We exist to deploy technologies that make a measurable difference in tackling these problems.
We are looking for machine learning engineers to build and deploy repeatable data and machine learning pipelines, webapps and end to end systems for AI products on our banking client’s GCP infrastructure. You’ll be involved in defining and automating with diverse datasets as you explore and understand the data and domain.
We are strong believers in high quality software delivery alongside and an engineering led approach to consulting. You don’t need to be an expert in financial crime, but you do need the intellectual curiosity to learn more.
Delivering software into production environments with an emphasis on data processing or MLOps.
Experience developing data transformations on large scale data platforms, either relational or non-relational.
Ad-hoc data analysis and data exploration
Experience debugging data processes, resolving and articulating problems with data and performance optimization.
Solving and implementing practical strategies for system and architecture design, preferably within financial services or another complex or regulated industry.
Experience of financial crime and transaction monitoring
Experience of working with managed machine learning APIs.
Proficiency with python in an organized code base for data pipelines and machine learning.
Proficiency with data manipulation languages and carrying out data analysis and hypothesis testing - Advanced SQL OR python
Experience with "big data" technologies and data platforms - we use bigquery, apache ibis, sqlglot, DBT. Fluency with unix or macos shells, ssh
Shell and docker Unix/Docker - Data platforms, e.g. cloud or hadoop - Google Cloud Platform, AML AI
API based machine learning solutions - we use Google's AML AI.
Other "Full-stack" experience, particular with webapps - react, next.js
Lead deployment models and solutions onto client environments by transforming and exploring client data on their systems.
Drive the development of robust, repeatable and deployable data and MLOps pipelines to tune, train and predict.
Working with the co-founders, prioritise and implement additional data and features to improve our success metrics.
Language
~ English fluency essential
Hybrid Working - 2/3 days in the office in London.
~£Pension contributions - 3% contribution match
~ Bonus up to 15% of base salary, dependent on company performance
~25 days holiday