At a Glance
- Tasks: Drive AI infrastructure, design multi-agent systems, and deploy AI features at scale.
- Company: Join Model ML, a fast-growing AI platform transforming financial workflows.
- Benefits: Competitive salary, remote work options, and opportunities for professional growth.
- Other info: Dynamic team environment with mentorship opportunities and career advancement.
- Why this job: Make an impact in AI while working with top investors and innovative technologies.
- Qualifications: 5+ years in software engineering with strong backend skills and AI application experience.
The predicted salary is between 63000 - 77000 £ per year.
Company Overview
Model ML is the AI workflow builder transforming how major financial institutions produce and validate client-ready work.
Model ML converts complex, manual processes into fully automated AI systems that scale across global teams.
In under a year, Model ML has become one of the fastest growing enterprise AI platforms worldwide and recently closed a $75 million Series A, one of the largest fintech Series A rounds ever.
The round was backed by FT Partners, Y Combinator, Local Globe, QED, 13books, and other top global investors, bringing total funding to $90 million.
Member of Technical Staff - AI
Model ML is the AI workflow builder transforming how major financial institutions produce and validate client-ready work.
Model ML converts complex, manual processes into fully automated AI systems that scale across global teams.
In under a year, Model ML has become one of the fastest growing enterprise AI platforms worldwide and recently closed a $75 million Series A, one of the largest fintech Series A rounds ever.
The round was backed by FT Partners, Y Combinator, Local Globe, QED, 13books, and other top global investors, bringing total funding to $90 million.
About the role
In this role, you will own and drive large portions of our AI agent infrastructure, from designing and deploying multi-agent systems to integrating Retrieval-Augmented Generation (RAG) pipelines, and evaluation frameworks.
You will be responsible for delivering AI-powered features into production at scale - ensuring they are performant, reliable, and secure - while also contributing across the stack, from frontend interfaces to backend APIs, databases, and deployment pipelines.
- Job Responsibilities
- Build, test, and deploy backend services and APIs (Python/ Django/ Fast API preferred, but other languages/frameworks welcome).
- Collaborate with founders, growth team, designers, and other engineers to deliver high-impact features.
- Ensure scalability, performance, and security across the stack.
- Develop and deploy AI-powered features in production, including RAG (Retrieval-Augmented Generation) systems, multi-agent infrastructure, and evaluation frameworks (Evals).
- Create data pipelines for AI model training, evaluation, and continuous improvement.
- Mentor junior developers and promote engineering best practices.
- Job Requirements
- 5+ years of professional software engineering experience.
- Hands-on experience building and deploying AI applications in production environments.
- Strong backend development skills (Python preferred)
- Solid understanding of relational databases.
- Experience with Git and collaborative development workflows.
- Knowledge of cloud infrastructure, containerization (Docker, Kubernetes), and CI/CD pipelines.
- Strong problem-solving skills and a passion for building great products.
- Experience implementing background workers and task queues (Celery, RQ, etc.).
- Proficiency with Redis for caching, pub/sub, or job queues.
- Hands-on experience building and deploying AI applications in production environments.
- Experience implementing RAG pipelines, AI agent orchestration, and performance monitoring.
- Familiarity with LLM evaluation techniques and tools for measuring model accuracy, reliability, and safety.
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Member of Technical Staff - AI in London employer: Model ML
Model ML is an exceptional employer, offering a unique opportunity to work at the forefront of AI innovation in the heart of London. With direct access to experienced founders and a culture that prioritises high trust and impact, employees can expect to grow rapidly while shaping the future of enterprise AI marketing. The competitive salary, meaningful equity, and performance-based incentives further enhance the appeal of joining a team dedicated to building something iconic.
StudySmarter Expert Advice🤫
We think this is how you could land Member of Technical Staff - AI 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 Model ML 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 Model ML.
✨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 Model ML.
✨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 Model ML 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 Member of Technical Staff - AI 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 Model ML.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Model ML 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 Model ML
✨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 Model ML 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.