Machine Learning Engineer

Machine Learning Engineer

Full-Time 60000 - 80000 £ / year (est.) No working from home possible
TradingHub

At a Glance

  • Tasks: Design and develop machine learning models for advanced financial analytics.
  • Company: Join TradingHub, a leader in intelligent trade surveillance software.
  • Benefits: Enjoy hybrid working, private medical insurance, and generous leave policies.
  • Other info: Diverse and inclusive workplace with excellent growth opportunities.
  • Why this job: Be the first dedicated ML engineer and make a real impact in finance.
  • Qualifications: Strong Python skills and experience with modern ML frameworks required.

The predicted salary is between 60000 - 80000 £ per year.

Compensation: Competitive (Financial Services)

About TradingHub

Founded in 2010, TradingHub delivers uniquely intelligent trade surveillance software to world leading financial institutions. Developed by market professionals, our solutions use sophisticated modelling techniques to detect single and cross-product market manipulation. With a team of over 150 experts worldwide, TradingHub combines global reach with deep markets expertise to help our customers mitigate financial, regulatory, and reputational risk.

The Role

We are looking for a Machine Learning Engineer to join our Analytics division and play an important role in enhancing our metrics offering. As our first dedicated ML hire, you’ll be utilising an array of modern LLM and NLP techniques to analyse complex financial data and unlock new capabilities for our market-leading suite of trade surveillance products. This role will see you combine hands-on model development and software engineering, and collaborate with a high-performing team of Quant Researchers and Developers as well as other cross-functional departments.

Responsibilities

  • Design, develop, and deploy machine learning models to enhance TradingHub’s market surveillance and analytics platform
  • Contribute to the development of advanced metrics used to analyse trader behaviour, order execution and potential market abuse scenarios
  • Apply machine learning and statistical techniques to large-scale financial datasets, improving accuracy and reducing false positives
  • Leverage LLM and NLP models to extract insights from unstructured data and integrate them into existing analytics workflows
  • Collaborate closely with quantitative developers, data engineers, and product teams to productionise models into scalable, high-performance systems

Requirements

  • Confident programming skills in Python, with experience using modern ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn)
  • Good understanding of core machine learning concepts such as linear regression, reinforcement learning and deep learning
  • Industry experience using Large Language Models (LLMs) to deliver commercial value
  • Experience building data pipelines and performing feature engineering on real-world datasets
  • Strong problem-solving skills and attention to detail
  • Good understanding of SQL and working with complex datasets
  • Keen interest in financial markets e.g. pricing, trading, fixed income

Benefits

Life at TradingHub is a rewarding journey within a fast-growing company that thrives on innovation and collaboration. By combining the best of technology and global markets, we’re able to solve complex problems together and deliver meaningful results to our customers. Everybody has value to bring, and we welcome individuality as a key driving force behind our collective success. Rooted in everything that we do are our core values: Accountability, Ambition, Partnership and Trust. These values provide the foundation for a sustainable workplace culture that empowers you to grow, contribute, and become your best self.

Employee Benefits

  • Annual discretionary performance bonus (permanent employees only)
  • Hybrid working policy
  • Office lunches twice a week
  • Private medical insurance + dental cover
  • Extended parental leave (up to 6 months of fully paid maternity leave)
  • 25 days annual leave + bank holidays
  • Enhanced company pension plan
  • 5 days study leave towards professional qualifications
  • Salary sacrifice schemes
  • Death in service coverage

Don’t tick every single requirement? Research shows that candidates from under-represented groups are less likely to apply unless they meet all the criteria. We are dedicated to building a diverse, equitable and inclusive workplace, so if this role excites you, please don’t let our specification hold you back. Get in touch!

Equal Opportunity Statement

TradingHub is an equal opportunities employer. We do not discriminate based on race, religion, ethnic or national origins, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, socio-economic background, responsibilities for dependants, physical or mental disability or other applicable legally protected characteristics. TradingHub selects candidates for interview solely on their skills, experience and qualifications. We are committed to making our recruitment process accessible to all and we encourage candidates to inform us of any required adjustments. A full copy of our diversity, equity and inclusion policy will be made available to you upon request.

Machine Learning Engineer employer: TradingHub

At TradingHub, we pride ourselves on being an exceptional employer that fosters innovation and collaboration within the fast-paced financial services sector. Our commitment to employee growth is evident through our comprehensive benefits package, including a hybrid working policy, generous parental leave, and support for professional development. Join us in a culture that values accountability, ambition, partnership, and trust, where your unique contributions are celebrated and you can thrive in your career as a Machine Learning Engineer.

TradingHub

Contact Details:

TradingHub Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Machine Learning Engineer

Tip Number 1

Network like a pro! Reach out to current employees at TradingHub on LinkedIn or other platforms. A friendly chat can give you insider info and might just get your foot in the door.

Tip Number 2

Show off your skills! Prepare a portfolio showcasing your machine learning projects, especially those using LLMs and NLP techniques. This will help you stand out during interviews.

Tip Number 3

Practice makes perfect! Brush up on your Python programming and ML frameworks like PyTorch and TensorFlow. Being confident in these areas will boost your chances of impressing the hiring team.

Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the TradingHub team.

We think you need these skills to ace Machine Learning Engineer

Machine Learning
Natural Language Processing (NLP)
Large Language Models (LLMs)
Python Programming
PyTorch
TensorFlow
scikit-learn

Some tips for your application 🫡

Show Off Your Skills:When you're writing your application, make sure to highlight your programming skills in Python and any experience with ML frameworks like PyTorch or TensorFlow. We want to see how you can bring your technical expertise to the table!

Connect the Dots:Don’t just list your experiences; explain how they relate to the role. If you've worked with LLMs or NLP techniques, share specific examples of how you’ve used them to solve problems or improve processes. This helps us see your thought process!

Be Yourself:We value individuality, so let your personality shine through in your application. Share your passion for financial markets and how it drives your work. This is your chance to show us what makes you unique!

Apply Through Our Website:Make sure to submit your application through our website. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it’s super easy!

How to prepare for a job interview at TradingHub

Know Your ML Stuff

Brush up on your machine learning concepts, especially linear regression, reinforcement learning, and deep learning. Be ready to discuss how you've applied these techniques in real-world scenarios, particularly in financial contexts.

Showcase Your Coding Skills

Make sure you're comfortable with Python and familiar with frameworks like PyTorch and TensorFlow. During the interview, you might be asked to solve coding problems or explain your previous projects, so have examples ready that highlight your programming prowess.

Understand Financial Markets

Since this role is in financial services, having a keen interest in pricing, trading, and market behaviour will set you apart. Be prepared to discuss how your machine learning skills can enhance trade surveillance and analytics in this sector.

Collaborate and Communicate

This position involves working closely with Quant Researchers and Developers. Highlight your teamwork experiences and how you've successfully collaborated on projects. Good communication skills are key, so practice explaining complex concepts in simple terms.