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- Tasks: Build and deploy machine learning pipelines and web apps for financial crime solutions.
- Company: Join Groundtruth AI, a young company transforming financial crime detection with cutting-edge technology.
- Benefits: Enjoy hybrid work, competitive salary, pension contributions, and up to 25 days holiday.
- Why this job: Work closely with co-founders in a dynamic environment and make a real impact on financial crime.
- Qualifications: 3+ years in software delivery, data processing, and MLOps; proficiency in Python and SQL required.
- Other info: Opportunity to grow with a startup and explore novel technologies in a supportive team.
The predicted salary is between 52000 - 78000 £ per year.
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About Groundtruth AI
Groundtruth AI was founded in 2024 and is about to celebrate its first year. We’ve grown from 2 people to 4 in the last year and have made considerable progress already.
We are hiring for Groundtruth AI Ltd.
Senior Machine Learning Engineer
Groundtruth AI is 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.
Who are we looking for?
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 a young company, and you will be working with the co-founders from the very start. You will have a demonstrable track record of getting things done in environments where the objectives are sometimes ambiguous. You will be comfortable with working with novel technologies and techniques as you go along, and owning a problem from end to end.
We are strong believers in high-quality software delivery alongside 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.
Experience
These experience levels are a minimum and we’re recruiting across a range of experience levels for the right person.
3+ years experience of:
- Delivering software into production environments with an emphasis on data processing or MLOps.
- Working as part of a development team with version control technologies.
- 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.
Desirable
- Experience of financial crime and transaction monitoring.
- Experience of working with managed machine learning APIs.
Tech stack
We expect to test some of these during the interview process.
Must
- 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. You might have experience with Hadoop, Hive, Redshift, Snowflake, Spark or similar.
- Experience with Version control/CI/CD – we use Git and GitHub Actions.
- Fluency with Unix or macOS shells, SSH.
- Shell and Docker – Data platforms, e.g., cloud or Hadoop – Google Cloud Platform, AML AI.
Desirable
- API-based machine learning solutions – we use Google’s AML AI.
- Other “Full-stack” experience, particularly with web apps – React, Next.js.
Responsibilities
- 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.
- Creatively adapt to a range of different client technologies.
- Working with the co-founders, prioritize and implement additional data and features to improve our success metrics.
Education
Quantitative ability, either through a formal education in a quantitative subject or equivalent experience. Understanding, designing, and articulating how to evaluate models is a part of the role.
Language
- English fluency essential.
Benefits
- Hybrid Working – 2/3 days in the office in London.
- £65k-£95k
- Pension contributions – 3% contribution match
- Bonus up to 15% of base salary, dependent on company performance
- 25 days holiday.
Visa Sponsorship
We regret that we do not currently hold a Visa Sponsorship Licence though we are continuing to apply for one.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Human Resources Services
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Senior Machine Learning Engineer employer: Find Next Hire
Contact Detail:
Find Next Hire Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Make sure to showcase your experience with data processing and MLOps in your conversations. Highlight specific projects where you've successfully delivered software into production environments, as this aligns closely with what Groundtruth AI is looking for.
✨Tip Number 2
Familiarize yourself with the tech stack mentioned in the job description, especially Google Cloud Platform and big data technologies like BigQuery. Being able to discuss your hands-on experience with these tools will demonstrate your readiness for the role.
✨Tip Number 3
Prepare to discuss your problem-solving skills, particularly in ambiguous situations. Groundtruth AI values candidates who can own a problem from end to end, so think of examples where you've navigated challenges effectively.
✨Tip Number 4
Show your intellectual curiosity about financial crime and transaction monitoring. Even if you don't have direct experience, expressing a genuine interest in learning more about the domain can set you apart from other candidates.
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, data processing, and MLOps. Emphasize your proficiency with Python and any big data technologies you've worked with, as these are crucial for the role.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for Groundtruth AI and its mission to combat financial crime. Mention specific projects or experiences that demonstrate your ability to work with ambiguous objectives and novel technologies.
Showcase Your Problem-Solving Skills: Provide examples of how you've tackled complex problems in previous roles. Highlight your experience with debugging data processes and optimizing performance, as these skills are essential for the position.
Highlight Your Team Collaboration: Since you'll be working closely with co-founders and a small team, emphasize your experience in collaborative environments. Discuss how you've contributed to team success and adapted to different technologies in past projects.
How to prepare for a job interview at Find Next Hire
✨Showcase Your Technical Skills
Be prepared to demonstrate your proficiency in Python and SQL during the interview. You might be asked to solve problems or analyze data on the spot, so brush up on your coding skills and be ready to discuss your previous projects involving data pipelines and MLOps.
✨Understand the Company’s Mission
Groundtruth AI is focused on tackling financial crime using innovative technologies. Familiarize yourself with their mission and be ready to discuss how your experience aligns with their goals, especially in the context of financial services and data processing.
✨Prepare for Problem-Solving Questions
Expect questions that assess your ability to handle ambiguous situations and solve complex problems. Think of examples from your past work where you successfully navigated challenges, particularly in data analysis or system design.
✨Demonstrate Your Curiosity
While expertise in financial crime isn't required, showing intellectual curiosity about the field can set you apart. Be prepared to discuss what you've learned about financial crime and how you plan to continue expanding your knowledge in this area.
