Level

LSEG

Machine Learning Engineer

AI in this role

ragml-opsai-automationnlpai-safety

About the Role

At LSEG, we are building AI-powered solutions that help teams solve meaningful operational and business challenges. We are looking for a Machine Learning Engineer who is curious, collaborative, and excited to apply machine learning and generative AI to real-world business problems.

As part of our Innovation & Intelligence team, you will work alongside data scientists, engineers, product teams, and business stakeholders to design and deliver AI solutions that create measurable value. You will contribute across the full solution lifecycle, from exploration and experimentation through deployment, monitoring, and continuous improvement.

We welcome candidates from a variety of backgrounds and experiences. Whether your expertise comes from industry projects, research, academic work, open-source contributions, hackathons, or personal initiatives, we encourage you to apply.

 

About the Team

The Innovation & Intelligence team applies artificial intelligence, machine learning, advanced analytics, and automation to improve processes, enhance decision-making, and strengthen customer outcomes .

We believe innovation comes from diverse experiences, perspectives, and ideas. Every team member is encouraged to contribute, learn, challenge assumptions, and help shape solutions that solve real business problems.

We are committed to creating an inclusive environment where everyone can thrive, grow their skills, and make an impact.

We welcome applications from candidates of all backgrounds and experiences.

 

Key Responsibilities

  • Design, develop, and deploy machine learning and AI-powered solutions that address business challenges and deliver measurable outcomes.
  • Partner with business, operations, and technology teams to understand opportunities and translate requirements into scalable solutions.
  • Develop, evaluate, and refine proof-of-concepts, prototypes, and minimum viable products (MVPs) to validate ideas and accelerate innovation.
  • Build and maintain data pipelines, model inference pipelines, and automation workflows that support production-ready AI solutions.
  • Apply machine learning, information retrieval, natural language processing, and generative AI techniques to improve business processes and user experiences.
  • Contribute to engineering best practices including testing, monitoring, documentation, security, and continuous improvement.
  • Collaborate effectively with colleagues across functions to share knowledge, solve problems, and deliver high-quality outcomes.
  • Continuously learn and explore emerging technologies, tools, and techniques in artificial intelligence, machine learning, cloud computing, and automation.

 

Required Skills and Experience

Essential

  • Experience developing, implementing, or supporting machine learning, artificial intelligence, or advanced analytics solutions.
  • Proficiency in Python and familiarity with software engineering best practices.
  • Experience working with SQL and data-driven applications.
  • Experience working with cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform.
  • Understanding of machine learning lifecycle management, model deployment, and MLOps practices.
  • Analytical thinking skills with the ability to solve complex business and technical problems.
  • Ability to communicate technical concepts clearly to both technical and non-technical audiences.
  • Experience collaborating effectively within cross-functional teams.
  • A growth mindset with a passion for learning and applying new technologies.

Preferred

  • Experience working with Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), vector databases, or agent-based AI systems.
  • Exposure to model monitoring, observability, AI governance, and responsible AI practices.
  • Knowledge of APIs, containerization technologies, CI/CD pipelines, and modern software development practices.
  • Experience delivering AI or data science solutions in an enterprise environment.
  • Familiarity with information retrieval, search technologies, and knowledge management solutions.

 

What We Offer

  • The opportunity to work on high-impact AI and machine learning solutions used across a global organization.
  • Exposure to cutting-edge technologies including Generative AI, Agentic AI, Machine Learning, and Intelligent Automation.
  • Collaboration with experienced data scientists, engineers, architects, and business leaders.
  • Continuous learning and professional development opportunities.
  • An inclusive and supportive environment where diverse perspectives are valued and innovation is encouraged.
  • The opportunity to make a measurable impact on business outcomes and customer experiences at scale.

 

We Encourage You to Apply

We recognize that no candidate matches every qualification listed in a job description.

If you do not meet every qualification but believe your skills and experience would enable you to succeed in this role, we encourage you to apply. We value potential, curiosity, continuous learning, and diverse perspectives as much as technical expertise.


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.

LSEG is a leading global financial markets infrastructure and data provider. Our purpose is driving financial stability, empowering economies and enabling customers to create sustainable growth.

Our purpose is the foundation on which our culture is built. Our values of Integrity, Partnership, Excellence and Change underpin our purpose and set the standard for everything we do, every day. They go to the heart of who we are and guide our decision making and everyday actions.

Working with us means that you will be part of a dynamic organisation of 25,000 people across 65 countries. However, we will value your individuality and enable you to bring your true self to work so you can help enrich our diverse workforce.

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. Conforming with applicable law, we can reasonably accommodate applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.

You will be part of a collaborative and creative culture where we encourage new ideas. We are committed to sustainability across our global business and we are proud to partner with our customers to help them meet their sustainability objectives. Our charity, the LSEG Foundation provides charitable grants to community groups that help people access economic opportunities and build a secure future with financial independence. Colleagues can get involved through fundraising and volunteering.

LSEG offers a range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives.

Please take a moment to read this privacy notice carefully, as it describes what personal information London Stock Exchange Group (LSEG) (we) may hold about you, what it’s used for, and how it’s obtained, your rights and how to contact us as a data subject.

If you are submitting as a Recruitment Agency Partner, it is essential and your responsibility to ensure that candidates applying to LSEG are aware of this privacy notice.

How we rate this

Machine Learning Engineer at LSEG rates 64 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RAGML OpsAI AutomationNLPAI Safety

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you monitor a model once it's live, and how do you know it needs retraining?
  3. Tell me about a workflow you automated with AI tools, end to end.
  4. What NLP problem have you worked on, and how did you measure whether it actually worked?
  5. How do you think about the risk of an AI system in this kind of role failing silently?

Adapt your resume

  • List these exact terms on your resume: RAG, ML Ops, AI Automation, NLP, and AI Safety. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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