At a Glance
- Tasks: Build and evolve AI systems that power investment insights for professional investors.
- Company: Dynamic fintech company focused on real market impact and innovation.
- Benefits: Competitive salary, equity options, and a collaborative in-office environment.
- Other info: Enjoy real ownership, technical autonomy, and support from senior peers.
- Why this job: Directly influence investor decisions and tackle challenging AI problems.
- Qualifications: 5+ years in ML or AI systems, strong Python skills, and startup experience.
The predicted salary is between 90000 - 160000 £ per year.
You have built real AI systems that ship, break, and get fixed under pressure. You care less about model demos and more about decisions that move capital. You want your work used daily by professional investors, not buried in notebooks. You are comfortable owning hard problems end to end. If you want a calm job optimizing benchmarks, this is not it.
The Role, In Plain English
You will build and evolve the AI systems that power Reflexivity's investment insights. This role exists because off-the-shelf models and generic pipelines are not enough. You will work at the intersection of reasoning engines, proprietary data, and real market impact. Your work directly affects how investors understand earnings, risk, and market catalysts.
What You'll Be Responsible For
- Design, fine-tune, and deploy ML and LLM-driven systems used in production by professional investors
- Build and maintain inference pipelines that are fast, observable, and reliable
- Integrate OpenAI, Gemini, and Anthropic models into reasoning and knowledge systems
- Work closely with backend engineers to productionize models in Golang-based services
- Improve signal quality, not just model accuracy
- Review code and designs with a bias toward long-term maintainability
What 'Good' Looks Like in This Role
After 3 months: You understand the product, data flows, and investor use cases deeply. You ship meaningful improvements.
After 6 months: You own major parts of the AI stack. Your work improves insight quality and latency measurably.
After 12 months: You are a technical reference point for AI decisions. You raise the bar for how AI is built at Reflexivity.
Who You Are (Must-Haves)
- 5 plus years building ML or applied AI systems in production
- Startup experience working on a core product, not a side project
- Strong Python skills and experience integrating with backend systems
- Hands-on experience with AI-assisted coding tools like Cursor or Claude Code
- Fintech experience or strong personal investment background
- Comfortable owning outcomes, not just tasks
Nice-to-Haves (Not Deal Breakers)
- Experience with LLM reasoning systems or knowledge graphs
- Exposure to Golang-based ML integrations
- Prior experience supporting investor-facing products
How We Work
- In-office team with high trust and high ownership
- Direct communication, minimal process, strong opinions backed by data
- Engineers are expected to think about product impact, not just code
- We move fast when it matters and slow down when correctness matters more
Why This Role Is Worth Your Time
- Direct influence on how professional investors make decisions
- Hard problems at the edge of AI, data, and finance
- Real ownership and technical autonomy
- Senior peers who care about quality and outcomes
Compensation & Practicalities
Base salary: £90,000 to £160,000 depending on experience. Equity included. In-office role based in London. No agency candidates.
Machine Learning and AI Engineer - London employer: Reflexivity
Reflexivity is an exceptional employer for Machine Learning and AI Engineers, offering a dynamic work environment in London where innovation meets finance. With a culture of high trust and ownership, employees are empowered to tackle challenging problems that directly impact professional investors' decision-making. The company prioritises real-world applications of AI, providing ample opportunities for personal and professional growth while fostering collaboration with senior peers who value quality and outcomes.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning and AI Engineer - London
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the AI and finance space. Attend meetups, conferences, or even online webinars. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those that have made a real impact. Share it on platforms like GitHub or your personal website. This way, potential employers can see your work in action and understand how you tackle hard problems.
✨Tip Number 3
Prepare for interviews by diving deep into the company’s products and data flows. Understand their challenges and think about how you can contribute. When you walk in, you want to show them you’re not just another candidate; you’re the one who can help them build better AI systems.
✨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 and take the initiative to reach out directly.
We think you need these skills to ace Machine Learning and AI Engineer - London
Some tips for your application 🫡
Show Your Real-World Experience:When you're writing your application, make sure to highlight any real AI systems you've built that have been used in production. We want to see how you've tackled hard problems and delivered results under pressure, so don't hold back on the details!
Focus on Impact, Not Just Tasks:In your written application, emphasise how your work has made a difference. We care about decisions that move capital, so share examples of how your contributions have directly impacted investors or improved processes.
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and fluff. Make it easy for us to see why you’re a great fit for the role without wading through unnecessary information.
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 don’t miss out on any important updates. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Reflexivity
✨Know Your AI Systems Inside Out
Make sure you can discuss the AI systems you've built in detail. Be ready to explain how they work, the challenges you faced, and how you overcame them. This role is all about real-world applications, so focus on your hands-on experience rather than theoretical knowledge.
✨Showcase Your Problem-Solving Skills
Prepare examples of hard problems you've tackled in previous roles. Highlight your thought process and the impact of your solutions. The interviewers will want to see that you can own outcomes and not just tasks, so be clear about how your contributions made a difference.
✨Understand the Financial Context
Brush up on your fintech knowledge and be ready to discuss how AI impacts investment decisions. Familiarise yourself with market catalysts and risk assessment, as this role directly affects how investors operate. Showing that you understand the financial implications of your work will set you apart.
✨Communicate Clearly and Confidently
Since this role involves working closely with backend engineers and other teams, practice articulating your ideas clearly. Use straightforward language to explain complex concepts, and don’t hesitate to ask questions if something isn’t clear. Good communication is key in a fast-paced environment like this.
