At a Glance
- Tasks: Design and deploy advanced machine learning models for quantitative trading.
- Company: High-performing quantitative trading firm with a tech-driven culture.
- Benefits: Competitive salary up to £200,000 plus equity and remote work flexibility.
- Other info: Join a team of exceptional engineers and researchers while enjoying excellent career growth.
- Why this job: Make a real impact on trading performance from day one in a fast-paced environment.
- Qualifications: Degree in a quantitative field and strong experience with machine learning in Python.
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. This is a hands-on role within a fast-moving, technology-led environment where your work will have a measurable impact from day one. While the role is fully remote, candidates must be based in the UK and willing to attend occasional team gatherings and meetings.
The Role
- 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.
Requirements
- 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.
- Strong understanding of statistics, probability, optimisation, and quantitative modelling techniques.
- Experience working with high-volume datasets and designing scalable research or production pipelines.
- Proven ability to take models from research through to live deployment.
- A track record of solving complex quantitative problems in fast-paced environments.
Desirable Experience
- Experience within quantitative trading, hedge funds, systematic investing, market making, or financial technology.
- Knowledge of alpha generation, factor modelling, portfolio optimisation, or execution modelling.
- 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.
If this opportunity is of interest, please apply below.
Senior Machine Learning Engineer in Nottingham employer: Platform Recruitment
Join a leading quantitative trading firm that champions innovation and excellence in machine learning. With a fully remote work culture, you will collaborate with top-tier professionals in a dynamic environment that values your contributions and offers substantial growth opportunities. Enjoy competitive compensation, equity options, and the chance to make a significant impact on financial markets from the comfort of your home in the UK.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer in Nottingham
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. This is your chance to demonstrate what you can do beyond just a CV.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your past projects in detail. We want to see how you think and solve problems.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love hearing from passionate candidates like you!
We think you need these skills to ace Senior Machine Learning Engineer in Nottingham
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with machine learning models and quantitative analysis. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about machine learning in finance and how you can contribute to our team. Keep it concise but impactful – we love a good story!
Showcase Your Technical Skills:Don’t forget to mention your proficiency in Python and any frameworks like PyTorch or TensorFlow. We’re looking for hands-on experience, so include specific examples of projects where you’ve built predictive models or worked with large datasets.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Plus, it’s super easy!
How to prepare for a job interview at Platform Recruitment
✨Know Your Stuff
Make sure you brush up on your machine learning knowledge, especially around the frameworks mentioned like PyTorch, JAX, and TensorFlow. Be ready to discuss your past projects in detail, focusing on how you developed and deployed models, as this will show your hands-on experience.
✨Understand the Business
Since this role is within a quantitative trading firm, it’s crucial to understand the basics of trading and financial markets. Familiarise yourself with concepts like alpha generation and portfolio optimisation, so you can speak intelligently about how your work can impact trading performance.
✨Prepare for Technical Questions
Expect technical questions that test your understanding of statistics, probability, and optimisation techniques. Practise explaining complex concepts clearly and concisely, as you may need to communicate these ideas to non-technical team members.
✨Show Your Team Spirit
This role involves collaboration with various teams, so be prepared to discuss your experience working in cross-functional teams. Highlight any instances where you contributed to team success or helped solve complex problems together, as this will demonstrate your ability to thrive in a fast-paced environment.
