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For Companies At a Glance
- Tasks: Lead AI research and develop advanced deep learning models for financial forecasting.
- Company: Industry-leading hedge fund known for innovation and cutting-edge technology.
- Benefits: Competitive compensation, hybrid work model, and top-tier rewards package.
- Other info: Exciting opportunity to drive AI strategy in a dynamic, data-driven environment.
- Why this job: Shape the future of AI in finance and work with world-class experts.
- Qualifications: PhD or equivalent experience in AI, strong publication record, and deep learning expertise.
The predicted salary is between 80000 - 100000 £ per year.
I’m partnered with an industry-leading Hedge Fund that, after nearly 20 years of pioneering innovation and hiring some of the brightest minds in the market, is now looking to further its success through the latest advancements in deep learning. The firm has built its reputation on rigorous research and cutting-edge technology, and this hire will play a pivotal role in shaping the next generation of their quantitative research capabilities.
The Opportunity
This is a rare chance to take full ownership of the fund’s AI research strategy. You’ll have complete freedom to explore, design, and implement novel deep learning models to generate alpha across the fund. Working alongside world-class quants, you’ll define the long-term roadmap for deep learning at the fund - from foundational model research to production deployment.
What You’ll Do
- Lead the development of advanced deep learning frameworks for financial time-series forecasting and market modeling.
- Research, prototype, and evaluate cutting-edge architectures (e.g., GNNs, RNNs, Transformers) for signal discovery.
- Collaborate closely with data engineering and trading teams to translate research insights into scalable, production-grade models.
- Set and drive the fund’s overall AI strategy, identifying emerging techniques and trends in academia and industry.
- Present research internally and contribute to the firm’s broader innovation initiatives.
What They’re Looking For
- PhD (or equivalent research experience) in Artificial Intelligence, Data Science, Computer Science, Applied Mathematics, or a related field.
- A strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR.
- Hands-on experience applying deep learning models to complex, ideally temporal or financial, datasets.
- Expertise in Python and modern ML frameworks (TensorFlow, PyTorch, JAX, etc.).
- Prior experience in a commercial or industry setting post-PhD, ideally in a similarly data-driven domain.
Why Apply
- Compensation and total rewards package on par with top Big Tech firms.
- Opportunity to define the deep learning direction of one of the world’s most respected hedge funds.
- Hybrid model: 3–4 days a week onsite in Central London.
AI Research Lead employer: Block MB
Contact Detail:
Block MB Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Research Lead
✨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
Showcase your expertise! Create a portfolio of your deep learning projects and research. This will not only demonstrate your skills but also give you something tangible to discuss during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of deep learning frameworks and algorithms. Practice coding challenges and be ready to explain your thought process clearly.
✨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 seeing candidates who are proactive about their job search!
We think you need these skills to ace AI Research Lead
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI Research Lead role. Highlight your relevant experience in deep learning and any publications you've got under your belt. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about deep learning and how you can contribute to our innovative team. Be sure to mention specific projects or research that relate to the role.
Showcase Your Technical Skills: Don’t forget to highlight your technical expertise, especially in Python and ML frameworks like TensorFlow or PyTorch. We’re keen to see how you’ve applied these skills in real-world scenarios, so give us some juicy examples!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. We can't wait to see what you bring to the table!
How to prepare for a job interview at Block MB
✨Know Your Deep Learning Stuff
Make sure you brush up on the latest advancements in deep learning, especially those relevant to financial time-series forecasting. Be ready to discuss your past projects and how they relate to the role, showcasing your hands-on experience with models like GNNs, RNNs, and Transformers.
✨Show Off Your Research Skills
Prepare to talk about your publication record and any significant contributions you've made to top-tier conferences. This is your chance to highlight your expertise and how it aligns with the firm's focus on rigorous research and innovation.
✨Collaboration is Key
Since you'll be working closely with data engineering and trading teams, think of examples where you've successfully collaborated in the past. Emphasise your ability to translate complex research insights into practical applications, as this will be crucial for the role.
✨Have a Vision for AI Strategy
Be ready to discuss your thoughts on the future of AI in finance. What emerging techniques do you see as game-changers? Show that you can not only lead but also set a long-term roadmap for deep learning at the fund, demonstrating your strategic thinking.