At a Glance
- Tasks: Lead deep learning research and shape AI strategy in finance.
- Company: Forward-thinking financial organisation with a focus on innovation.
- Benefits: Competitive salary, performance bonuses, equity, and hybrid working.
- Other info: Mentorship opportunities and dedicated time for research and publishing.
- Why this job: Make a real impact by applying cutting-edge ML to financial markets.
- Qualifications: PhD in ML or related field, strong Python skills, and ML experience.
The predicted salary is between 80000 - 100000 € per year.
My client are a forward-thinking financial organisation looking for a Senior Research Engineer to own the machine learning strategy end to end. This is a rare opportunity to shape the AI direction from the ground up, from research through to production with direct visibility at the leadership level.
- Define and lead the deep learning research agenda, with a focus on time series modelling in financial markets
- Take models from research hypothesis all the way to production-grade, monitored systems
- Evaluate and apply cutting-edge academic research to real-world financial problems
- Work closely with quant researchers, engineers, and senior stakeholders to embed ML into core decision-making
- Help build and mentor a growing research team
- Published research in peer-reviewed venues such as IEEE, ICML, NeurIPS, ICLR, or equivalent
- Deep expertise in time series modelling - financial data experience strongly preferred
- Proven end-to-end ML experience: data pipelines, model development, deployment, and monitoring
- Strong Python and ML engineering skills (PyTorch or JAX)
- PhD in ML, Statistics, Computer Science, or related field (or equivalent research output)
- Experience in asset management, hedge funds, or quantitative trading
- Contributions to open-source ML projects
- Full ownership of ML strategy from day one
- Dedicated time and support for continued research and publishing
- Competitive base, performance bonus, and equity
- Hybrid working, flexible culture, and access to institutional-grade data and compute
Experienced Research Engineer in London employer: Block MB
Join a pioneering financial organisation that champions innovation and offers a unique opportunity to lead the machine learning strategy in a collaborative and flexible environment. With a strong emphasis on employee growth, you will have dedicated time for research and publishing, alongside competitive compensation and equity options. This role not only allows you to shape AI initiatives from inception to production but also provides direct visibility at the leadership level, making it an ideal place for those seeking meaningful and impactful work.
StudySmarter Expert Advice🤫
We think this is how you could land Experienced Research Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to deep learning and time series modelling. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Experienced Research Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Senior Research Engineer role. Highlight your deep learning expertise, time series modelling experience, and any relevant publications to catch our eye!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about machine learning and how you can contribute to shaping our AI direction. Share specific examples of your past work that demonstrate your end-to-end ML experience.
Showcase Your Research:If you've published research in peer-reviewed venues, make sure to mention it! We love seeing candidates who have contributed to the academic community, especially in areas related to financial markets and machine learning.
Apply Through Our Website:We encourage you to apply directly through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Block MB
✨Know Your Deep Learning Stuff
Make sure you brush up on your deep learning knowledge, especially around time series modelling. Be ready to discuss your past projects and how you've applied cutting-edge research to real-world problems, particularly in financial markets.
✨Showcase Your End-to-End ML Experience
Prepare to talk about your experience with the entire machine learning lifecycle. Highlight specific examples where you've taken models from research to production, including data pipelines and monitoring systems. This will show that you can own the ML strategy right from day one.
✨Engage with Stakeholders
Since you'll be working closely with quant researchers and senior stakeholders, think about how you can demonstrate your collaboration skills. Share examples of how you've successfully embedded ML into decision-making processes and how you’ve mentored others in your previous roles.
✨Bring Your Research to the Table
If you've published research in peer-reviewed venues, be prepared to discuss it! Talk about the impact of your work and how it relates to the role. This not only shows your expertise but also your commitment to advancing the field of machine learning.
