At a Glance
- Tasks: Define evaluation frameworks and build automated test pipelines for AI tools.
- Company: Join the innovative Corporate Engineering AI team at LSEG.
- Benefits: Enjoy healthcare, retirement planning, paid volunteering days, and wellbeing initiatives.
- Other info: Be part of a diverse team that values innovation and continuous improvement.
- Why this job: Make a significant impact in the AI ecosystem while advancing your career.
- Qualifications: Strong Python skills and experience in test automation and agentic systems.
The predicted salary is between 80000 - 100000 £ per year.
Corporate Engineering AI (CE AI) Team
The Corporate Engineering AI team is the central enablement and platform delivery function for LSEG’s internal agentic AI ecosystem.
The team’s mission is to scale safe, high‑quality AI capabilities across the enterprise by providing shared platforms, patterns, governance, and delivery support.
CE AI owns and operates core AI platforms including LSEG AI Assist, the Question Answering Service (QAS), and the Internal MCP Gateway.
Rather than delivering individual business use cases end‑to‑end, the team enables product engineering groups across LSEG to expose knowledge, data, and actions to AI agents in a consistent, governed, and repeatable way.
The team operates a Central MCP Delivery model: building critical MCP tools and services “for” product teams where required, while simultaneously defining standards, patterns, and platform capabilities that allow teams to progressively move towards self‑service contribution.
LSEG AI Assist / Internal MCP Programme of Work
This programme delivers an LSEG‑owned, production‑grade agentic AI platform with MCP as its extensibility layer.
The scope of work includes
- Building and operating LSEG AI Assist, an in‑house agentic experience capable of reasoning, planning, and tool‑calling.
- Operating QAS, the enterprise RAG and search layer used to ground agent responses in approved data sources.
- Delivering a production Internal MCP Gateway providing discovery, security, policy enforcement, observability, and lifecycle management for MCP tools and Skills.
- Designing and building MCP servers and Skills that expose internal and vendor systems safely to agents.
- Establishing evaluation, quality control, and governance mechanisms so MCP tools and Skills can be promoted through PTB/PTO and operated with confidence at scale.
The programme follows a “build for” model today, with a strong emphasis on defining the future product and platform experience, patterns, and contribution pathways that will enable federated scale over time.
Responsibilities
- Define and implement evaluation frameworks for MCP tools and Skills covering correctness, safety, and regression impact.
- Build and maintain automated test pipelines for agentic behaviours, including tool invocation and multi‑step workflows.
- Evaluate and mitigate agentic failure modes such as hallucination, tool misuse, invalid inputs, and latency amplification.
- Produce testing evidence required for Permit to Build (PTB) and Permit to Operate (PTO).
- Partner with ML Engineers to embed testability and evaluation hooks into MCP servers and Skills.
- Help define the long‑term quality and governance model for federated MCP contributions across LSEG.
Skills
- Strong Python experience for test harnesses and automation.
- Experience with LLM and RAG evaluation frameworks or custom evaluation pipelines.
- Test automation expertise covering unit, integration, and regression testing.
- Understanding of agentic system risks and failure modes.
- Ability to assess solutions against governance, security, and audit expectations.
- Experience working in regulated or highly governed engineering environments.
- Career Stage
- Senior Associate
- London Stock Exchange Group (LSEG) Information
Join us and be part of a team that values innovation, quality, and continuous improvement.
If you're ready to take your career to the next level and make a significant impact, we'd love to hear from you.
We are proud to be an equal opportunities employer.
This means that we do not discriminate on the basis of anyone’s race, religion, colour, national origin, gender, sexual orientation, gender identity, gender expression, age, marital status, veteran status, pregnancy or disability, or any other basis protected under applicable law.
LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives.
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Machine Learning Quality Engineer employer: LSEG
LSEG is an exceptional employer that fosters a dynamic and innovative work culture, perfect for those passionate about AI and technology. With a strong emphasis on employee growth, we offer numerous opportunities for professional development and collaboration on cutting-edge projects in a hybrid work environment. Join us in London to be part of a forward-thinking team that values creativity and technical expertise, making a meaningful impact in the world of finance and technology.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Quality Engineer
✨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 LSEG 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 LSEG.
✨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 LSEG.
✨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 LSEG 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 Machine Learning Quality Engineer
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 LSEG.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at LSEG 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 LSEG
✨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 LSEG 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.