Machine Learning Engineer (London)

Machine Learning Engineer (London)

London Full-Time 43200 - 72000 £ / 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 data analysis are essential.
  • Other info: CUBE promotes diversity and inclusivity, welcoming bold individuals ready to shape the future of compliance.

The predicted salary is between 43200 - 72000 £ 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 worlds top financial institutions globally.

In 2024, we achieved over 50% growth, both organically and through two strategic acquisitions. Were a fast-paced, high-performing team that thrives on pushing boundariescontinuously evolving our products, services, and operations. At CUBE, we dont 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. At CUBE, You will work alongside some of the brightest minds in AI research and engineering in developing impactful solutions that are reshaping the world of regulatory compliance.

Role Overview:

As ML Engineer, RegBrain, your mission is to:

  • Participate in the continuous improvement of RegBrains 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 of the Teams knowledge via demonstration and documentation.

Key Responsibilities:

As a machine learning engineer, your main responsibility is to conduct thedevelopment andproductionisationof ML and NLP-based features for CUBEs 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 withnew models and techniques.

  • Perform code-reviews for your colleagues 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 isdemonstrated 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 & DLplatforms,frameworks, and libraries.

  • Extensive experience with end-to-endmodel design and deploymentwithin cloud environments.

  • Asystems thinking approach, with passion for MLOps best practises.

  • 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.

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Machine Learning Engineer (London) employer: CUBE Content Governance Global Limited

CUBE is an exceptional employer for Machine Learning Engineers, offering a dynamic and innovative work environment in London. With a strong focus on personal and professional development, employees are empowered to take ownership of their careers while collaborating with some of the brightest minds in AI. The company's commitment to diversity, cutting-edge technology, and a culture that encourages boldness and ambition makes it an attractive place for those looking to make a meaningful impact in the regulatory compliance landscape.
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Contact Detail:

CUBE Content Governance Global Limited 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 RegPlatform and RegConnect. Understanding how these platforms operate will help you articulate how your skills in ML and NLP can directly contribute to their continuous improvement.

✨Tip Number 2

Engage with the ML and AI 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 highly valued at CUBE.

✨Tip Number 3

Prepare to discuss your experience with cloud-based ML engineering during the interview. Be ready to share specific examples of how you've implemented MLOps best practices and optimised ML models in previous roles.

✨Tip Number 4

Highlight your ability to work collaboratively in a team environment. CUBE values diversity and collaboration, so be prepared to discuss how you've successfully worked with others to achieve common goals in your past experiences.

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
End-to-End Model Design
MLOps Best Practices
Statistical Analysis
Code Review
Problem-Solving Skills
Collaboration and Teamwork
Adaptability to New Technologies

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, NLP, and cloud-based engineering. Use specific examples that demonstrate your proficiency in Python and any contributions to platforms like GitHub or Kaggle.

Craft a Compelling Cover Letter: In your cover letter, express your passion for regulatory technology and how your skills align with CUBE's mission. Mention specific projects or experiences that showcase your ability to develop advanced ML solutions.

Showcase Your Projects: If you have worked on relevant projects, especially those involving NLP or cloud environments, include links to your portfolio or GitHub. This will provide tangible evidence of your capabilities and experience.

Highlight Continuous Learning: CUBE values staying ahead in technology. Mention any recent courses, certifications, or research you’ve undertaken in ML or AI. This shows your commitment to continuous improvement and innovation in the field.

How to prepare for a job interview at CUBE Content Governance Global Limited

✨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 practical experience and proficiency.

✨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 technical questions related to ML, NLP, and cloud-based solutions. Brush up on your knowledge of algorithms, data structures, and best practices in MLOps to confidently tackle these queries.

✨Demonstrate Team Collaboration

CUBE values collaboration and diversity. Be prepared to discuss examples of how you've worked effectively in teams, shared knowledge, and contributed to a positive team culture in your previous roles.

Machine Learning Engineer (London)
CUBE Content Governance Global Limited
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