At a Glance
- Tasks: Collaborate with PhD researchers to develop and implement cutting-edge machine learning models.
- Company: Voleon, a leading tech company in AI and finance with a collaborative culture.
- Benefits: Competitive salary, daily catered lunches, modern office, and professional development opportunities.
- Other info: Dynamic environment with excellent career growth and the chance to work on innovative projects.
- Why this job: Join a team of experts and make a real impact in quantitative trading strategies.
- Qualifications: Bachelor's degree in a quantitative field and 5+ years of software engineering experience.
The predicted salary is between 63000 - 77000 £ per year.
Voleon is a technology company that applies state-of-the-art AI and machine learning techniques to real-world problems in finance. For nearly two decades, we have led our industry and worked at the frontier of applying AI/ML to investment management. We have become a multibillion-dollar asset manager, and we have ambitious goals for the future. Your colleagues will include internationally recognized experts in artificial intelligence and machine learning research as well as highly experienced finance and technology professionals. In addition to our enriching and collegial working environment, we offer highly competitive compensation and benefits packages, technology talks by our experts, a beautiful modern office, daily catered lunches, and more.
As a Senior Machine Learning Engineer on one of Voleon's Research teams, you will partner directly with research staff to advance our quantitative trading strategies. You will translate novel research ideas into production-quality code, build and maintain the data pipelines and modeling infrastructure that underpin our strategies, and apply your own strong mathematical intuition to solve open-ended technical challenges. This role lives at the boundary of research and engineering. You will be expected to understand the statistical and mathematical concepts your research partners work with, contribute meaningfully to technical discussions about model design and evaluation, and ensure that the resulting systems are performant, reliable, and maintainable. You will work at the intersection of Computer Science, Mathematics, and Statistics - building high-performance tools that enable world-class research while maintaining a high engineering standard.
Responsibilities
- Partner with PhD researchers to design, implement, and productize machine learning models that drive quantitative trading strategies
- Develop and maintain complex data pipelines, including data ingestion, feature engineering, validation, and quality monitoring
- Translate research prototypes and novel ideas into performant, well-tested, production-ready code
- Build extensible tools and frameworks that accelerate the model development and experimentation lifecycle
- Supervise, understand, and remediate subtle data quality issues across both research and production environments
- Proactively lead projects from requirements through delivery, making autonomous decisions about scope, dependencies, and trade-offs, with an emphasis on long-term maintainability
- Coordinate and contribute to deployment efforts while guiding junior engineers and researchers; align with research and engineering stakeholders on ownership, execution, and prioritization
- Foster engineering consistency, standards, and best practices within Research
Requirements
- Bachelor's degree (or higher) in Computer Science, Applied Mathematics, Statistics, or a related quantitative field
- 5+ years of professional software engineering experience, with strong CS fundamentals (data structures, algorithms, systems design)
- Demonstrated mathematical maturity - comfort with the concepts and notation used in statistics, linear algebra, optimization, and probability
- Deep proficiency in Python; experience with R and/or C/C++ is a strong plus
- Extensive experience with numerical and data science libraries (e.g., NumPy, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow, or similar)
- Proven experience building or maintaining machine learning systems in a distributed computing environment
- Proficiency developing in a Linux environment with attention to performance, correctness, and reproducibility
- Exceptional attention to detail, particularly when working with imperfect or heterogeneous data
- Strong verbal and written communication skills, and the ability to collaborate effectively with researchers whose primary expertise is not software engineering
Preferred Qualifications
- Experience with experiment management, model evaluation pipelines, or ML workflow orchestration
- Familiarity with modern ML/AI infrastructure patterns (model serving, feature stores, distributed training)
- Experience with performance profiling and optimization of numerical or modeling code
- Prior exposure to financial data, time-series analysis, or quantitative research environments
Senior Machine Learning Engineer in London employer: Voleon
Voleon is an exceptional employer that fosters a collaborative and innovative work culture in the heart of London. With a strong emphasis on employee growth, we provide ample opportunities for mentorship and professional development, ensuring that our team members thrive in their careers. Our commitment to cutting-edge technology and data-driven strategies makes Voleon a unique place to work, where your contributions directly impact our success in the dynamic world of quantitative trading.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Voleon or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Voleon.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Voleon.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Voleon that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Senior Machine Learning Engineer in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Voleon.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Voleon and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Voleon
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Voleon uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
