Machine Learning Engineer (London)
Machine Learning Engineer (London)

Machine Learning Engineer (London)

London Full-Time 48000 - 84000 ÂŁ / year (est.) No home office possible
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At a Glance

  • Tasks: Develop and improve AI-driven products for regulatory compliance using ML and NLP.
  • Company: CUBE is a leading RegTech firm revolutionising compliance with innovative SaaS solutions powered by AI.
  • Benefits: Enjoy a dynamic work culture, opportunities for personal growth, and the chance to work with cutting-edge technology.
  • Why this job: Join a fast-paced team that values innovation, collaboration, and making a real impact in the financial sector.
  • Qualifications: Proficiency in Python, experience with ML frameworks, and a passion for MLOps are essential.
  • Other info: CUBE promotes diversity and inclusivity, welcoming applicants from all backgrounds.

The predicted salary is between 48000 - 84000 ÂŁ per year.

CUBE are a global RegTech business defining and implementing the gold standard of regulatory intelligence for the financial services industry. We deliver our services through intuitive SaaS solutions, powered by AI, to simplify the complex and everchanging world of compliance for our clients.

Why us? CUBE is a globally recognized brand at the forefront of Regulatory Technology. Our industry-leading SaaS solutions are trusted by the world’s top financial institutions globally. In 2024, we achieved over 50% growth, both organically and through two strategic acquisitions. We’re a fast-paced, high-performing team that thrives on pushing boundaries—continuously evolving our products, services, and operations. At CUBE, we don’t just keep up we stay ahead. We believe our future is built by bold, ambitious individuals who are driven to make a real difference. Our “make it happen” culture empowers you to take ownership of your career and accelerate your personal and professional development from day one. With over 700 CUBERs across 19 countries spanning EMEA, the Americas, and APAC, we operate as one team with a shared mission to transform regulatory compliance. Diversity, collaboration, and purpose are the heartbeat of our success. We were among the first to harness the power of AI in regulatory intelligence, and we continue to lead with our cutting-edge technology.

Role Overview: As ML Engineer, RegBrain, your mission is to:

  • Participate in the continuous improvement of RegBrain’s products.
  • Develop advanced NLP and AI-based products that will delight users.
  • Provide excellence in cloud-based ML engineering, with as much focus on Operations as Development.
  • Expand the Team’s knowledge via demonstration and documentation.

Key Responsibilities: As a machine learning engineer, your main responsibility is to conduct the development and productionisation of ML and NLP-based features for CUBE’s products - a SaaS Platform (RegPlatform) and an API (RegConnect).

  • Develop optimal ML & NLP solutions for RegBrain use cases, from baseline to SOTA approaches, wherever appropriate.
  • Produce high quality, modular code, and deploy following our established DevOps CI/CD and best practices.
  • Improve the efficiency, performance, and scalability of ML & NLP models (this includes data quality, ingestion, loading, cleaning, and processing).
  • Stay up-to-date with ML & NLP research, and experiment with new models and techniques.
  • Perform code-reviews for your colleague’s code. Engage with them to raise standards of Software engineering.
  • Propose cloud architectures for ML-based products that need new infrastructure.
  • Participate in the monitoring and continuous improvement of existing ML systems.

Core requirements: Experience matters. But what is more important than raw number of years of experience is demonstrated proficiency (through GitHub profiles/online portfolios and the interview process itself). Bonus points for Stack Overflow and Kaggle contributions!

What we are looking for:

  • Experience analyzing large volumes of textual data (almost all of our use cases will involve NLP).
  • Ability to write clear, robust, and testable code, especially in Python.
  • Familiarity with SQL and NoSQL/graph databases.
  • Extensive experience with ML & DL platforms, frameworks, and libraries.
  • Extensive experience with end-to-end model design and deployment within cloud environments.
  • A systems thinking approach, with passion for MLOps best practices.
  • An engineer that can think in O(n) as much as plan the orchestration of their product.
  • Solid understanding of data structures, data modelling, and software architecture, especially cloud-based.
  • An engineer that can keep up with mathematically and statistically-oriented colleagues.
  • A healthy sense of humour.

Interested? If you are passionate about leveraging technology to transform regulatory compliance and meet the qualifications outlined above, we invite you to apply. Please submit your resume detailing your relevant experience and interest in CUBE.

CUBE is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Machine Learning Engineer (London) employer: CUBE

CUBE is an exceptional employer, offering a dynamic work environment in London where innovation and collaboration thrive. With a strong focus on personal and professional development, employees are empowered to take ownership of their careers while working alongside industry leaders in AI and regulatory technology. The company's commitment to diversity and inclusion, coupled with its rapid growth and cutting-edge projects, makes it an ideal place for those looking to make a meaningful impact in the financial services sector.
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Contact Detail:

CUBE Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Machine Learning Engineer (London)

✨Tip Number 1

Familiarise yourself with CUBE's products and services, especially their RegBrain platform. Understanding how they leverage AI and NLP in regulatory compliance will help you articulate your ideas and show genuine interest during discussions.

✨Tip Number 2

Engage with the ML and NLP community by contributing to platforms like GitHub or Kaggle. Showcasing your projects and contributions can demonstrate your proficiency and passion for machine learning, which is crucial for this role.

✨Tip Number 3

Prepare to discuss your experience with cloud-based ML engineering and DevOps practices. Be ready to share specific examples of how you've improved model performance and scalability in previous projects, as this aligns closely with the responsibilities of the role.

✨Tip Number 4

Network with current or former employees of CUBE on platforms like LinkedIn. Gaining insights into the company culture and expectations can give you an edge in understanding what they value in a candidate.

We think you need these skills to ace Machine Learning Engineer (London)

Machine Learning
Natural Language Processing (NLP)
Python Programming
Cloud Computing
DevOps CI/CD
Data Structures
Data Modelling
Software Architecture
SQL and NoSQL Databases
Deep Learning Frameworks
Model Deployment
MLOps Best Practices
Systems Thinking
Code Review Skills
Analytical Skills
Problem-Solving Skills

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, NLP, and cloud-based solutions. Use keywords from the job description to demonstrate that you meet the core requirements.

Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for regulatory technology and how your skills align with CUBE's mission. Mention specific projects or experiences that relate to the role of Machine Learning Engineer.

Showcase Your Work: Include links to your GitHub profile or online portfolio in your application. Highlight any contributions to Stack Overflow or Kaggle that demonstrate your proficiency in ML and NLP.

Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any spelling or grammatical errors. A polished application reflects your attention to detail and professionalism.

How to prepare for a job interview at CUBE

✨Showcase Your Projects

Make sure to highlight your previous work with machine learning and NLP projects. Bring along your GitHub profile or any online portfolio that showcases your contributions, as this will demonstrate your proficiency and hands-on experience.

✨Understand CUBE's Mission

Familiarise yourself with CUBE's goals and the regulatory technology landscape. Being able to discuss how your skills align with their mission to transform regulatory compliance will show your genuine interest in the role.

✨Prepare for Technical Questions

Expect to be asked about your experience with ML & DL platforms, cloud environments, and coding practices. Brush up on your knowledge of Python, SQL, and data structures, as well as MLOps best practices to impress your interviewers.

✨Demonstrate Team Collaboration

CUBE values collaboration and diversity, so be ready to discuss how you've worked effectively in teams. Share examples of how you've engaged with colleagues to improve code quality or share knowledge, as this aligns with their culture of continuous improvement.

Machine Learning Engineer (London)
CUBE
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  • Machine Learning Engineer (London)

    London
    Full-Time
    48000 - 84000 ÂŁ / year (est.)

    Application deadline: 2027-06-03

  • C

    CUBE

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