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 and technical autonomy in a fast-paced team.
- 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
At Reflexivity, we pride ourselves on being an exceptional employer that fosters a culture of innovation and ownership. Our London-based team thrives in a dynamic environment where your contributions directly impact professional investors' decision-making processes. With a focus on real-world applications of AI and ample opportunities for personal and professional growth, we empower our engineers to tackle challenging problems while enjoying the support of senior peers who are committed to 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 people in the industry. Attend meetups, conferences, or even online webinars. The more you engage, the better your chances of landing that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects and any real-world applications you've worked on. This is your chance to demonstrate how you can make an impact, just like we do at StudySmarter.
✨Tip Number 3
Prepare for those interviews! Research the company and its products thoroughly. Be ready to discuss how your experience aligns with their needs, especially around building and deploying ML systems. We want to see your passion!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in being part of our team at StudySmarter.
We think you need these skills to ace Machine Learning and AI Engineer - London
Some tips for your application 🫡
Show Your Real-World Impact:When you're writing your application, make sure to highlight any real AI systems you've built that have made a difference. We want to see how your work has been used in production and the impact it had on decision-making.
Be Specific About Your Skills:Don’t just list your skills; show us how you’ve applied them. If you’ve got strong Python skills or experience with AI-assisted coding tools, give us examples of how you’ve used these in past projects. We love specifics!
Emphasise Ownership and Problem-Solving:We’re looking for someone who owns their work and tackles hard problems head-on. In your application, share instances where you took charge of a project or solved a tough issue. This will help us see your fit for our fast-paced environment.
Apply Through Our Website:Make sure to submit your application through our website. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, we can’t wait to hear from you!
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 ready to demonstrate your ability to think critically under pressure.
✨Understand the Financial Context
Since this role directly affects how investors make decisions, brush up on your understanding of finance and investment principles. Be prepared to discuss how your work can improve insight quality and latency for professional investors. Showing that you grasp the financial implications of your work will set you apart.
✨Communicate Clearly and Confidently
In a fast-paced environment like this, clear communication is key. Practice explaining complex concepts in simple terms. Be direct and confident in your responses, and don’t hesitate to ask clarifying questions if needed. This shows that you value effective communication and are engaged in the conversation.
