At a Glance
- Tasks: Design and deploy advanced machine learning models for financial markets.
- Company: Join a high-performing quantitative trading firm with a remote-first culture.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Collaborate with top engineers and traders in a dynamic, innovative environment.
- Why this job: Make a real impact on trading performance using cutting-edge machine learning technology.
- Qualifications: Degree in a quantitative field and strong experience in Python ML frameworks.
The predicted salary is between 60000 - 80000 £ per year.
This is a unique opportunity for a Senior Machine Learning Engineer to join a high-performing quantitative trading firm building next-generation machine learning systems for financial markets. Working alongside a team of exceptional engineers, researchers, and traders, you will play a key role in developing models and infrastructure that directly influence trading performance and investment decisions.
While the role is fully remote, candidates must be based in the UK and willing to attend occasional team gatherings and meetings.
You will design, develop, and deploy advanced machine learning models across a range of quantitative trading and research initiatives. Working closely with trading, data, and engineering teams, you will help build scalable ML systems capable of extracting signals from large and complex datasets while contributing to the long-term technical direction of the platform.
- A degree (preferably MSc or PhD) in Mathematics, Statistics, Computer Science, Physics, Engineering, or a related quantitative discipline
- Strong commercial experience developing machine learning models in Python using frameworks such as PyTorch, JAX, or TensorFlow
- Experience building predictive models for time-series, forecasting, signal generation, or large-scale data analysis
- Proven ability to take models from research through to live deployment
- Experience within quantitative trading, hedge funds, systematic investing, market making, or financial technology
- Experience with reinforcement learning, probabilistic modelling, Bayesian methods, or deep learning for financial applications
- Familiarity with market data, alternative datasets, and low-latency or high-performance systems
Machine Learning Engineer - Hybrid employer: Platform Recruitment
Join a leading quantitative trading firm that champions innovation and excellence in the financial markets. As a Senior Machine Learning Engineer, you will thrive in a collaborative remote environment, where your contributions directly impact trading strategies and investment outcomes. With a strong focus on employee growth, cutting-edge technology, and a culture of teamwork, this role offers a unique opportunity to advance your career while working alongside some of the brightest minds in the industry.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer - Hybrid
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can get you in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. We recommend including any models you've built or data analyses you've conducted. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your past projects. We suggest practicing common ML interview questions and even doing mock interviews with friends.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented individuals like you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Machine Learning Engineer - Hybrid
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of a Senior Machine Learning Engineer. Highlight your experience with Python and any relevant frameworks like PyTorch or TensorFlow. We want to see how your skills align with our needs in quantitative trading!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and how your background fits into our team. We love seeing enthusiasm for the financial markets and innovative tech!
Showcase Your Projects:If you've worked on any cool projects, especially those involving predictive models or time-series analysis, make sure to mention them. We’re keen to see how you’ve taken models from research to live deployment, so don’t hold back!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our awesome team!
How to prepare for a job interview at Platform Recruitment
✨Know Your Stuff
Make sure you brush up on your machine learning concepts, especially those relevant to financial markets. Be ready to discuss your experience with frameworks like PyTorch or TensorFlow, and have examples of your predictive models at hand.
✨Showcase Your Projects
Prepare to talk about specific projects where you've taken models from research to live deployment. Highlight any challenges you faced and how you overcame them, as this will demonstrate your problem-solving skills and practical experience.
✨Understand the Company
Do a bit of homework on the firm’s trading strategies and the types of models they use. This will not only help you tailor your answers but also show that you're genuinely interested in their work and how you can contribute.
✨Ask Smart Questions
Prepare insightful questions about their current ML systems and future projects. This shows your enthusiasm for the role and gives you a chance to assess if the company aligns with your career goals.
