At a Glance
- Tasks: Design and build transformative ML systems that revolutionise financial analysis.
- Company: Join Fitch Ratings, a top credit ratings agency with a global impact.
- Benefits: Competitive salary, mentorship, and access to cutting-edge technology.
- Other info: Dynamic environment with clear growth paths and opportunities for technical leadership.
- Why this job: Be at the forefront of AI innovation and make a real difference in finance.
- Qualifications: 6+ years in ML engineering with strong Python skills and experience in generative AI.
The predicted salary is between 66150 - 80850 £ per year.
As one of the world's top three credit ratings agencies, Fitch Ratings plays a critical role in global capital markets by providing credit analysis, ratings, research, and commentary to financial market participants. For over 100 years, Fitch Ratings has been creating value for global markets through its rigorous analysis and deep expertise.
Fitch Ratings is seeking a Senior Machine Learning Engineer to join our new AI Innovation teams in London—where we're building the AI-powered future of financial analysis from the ground up. This is about designing and shipping breakthrough generative AI systems, agentic workflows, and intelligent platforms that will transform how credit analysis happens and how global financial markets operate.
As a Senior ML Engineer, you'll be a technical force on the team—building sophisticated ML systems, driving innovation through hands-on work, mentoring engineers, and helping establish the technical standards that will scale across the organization. We need ML engineers who thrive on hard problems and greenfield opportunities.
Build breakthrough ML systems with real impact: Design and ship production generative AI platforms, multi-agent systems, and intelligent automation that will process billions in credit decisions.
Work at the cutting edge of ML technology: Experiment with the latest LLMs and foundation models, implement novel RAG architectures, build agentic systems, fine-tune neural networks, and leverage enterprise-scale GPU clusters and cloud infrastructure.
Technical leadership without the bureaucracy: Lead projects, mentor junior engineers, shape technical direction, and influence architectural decisions through your expertise and results.
Toronto's world-class AI ecosystem: Work in one of the world's premier AI research hubs alongside Vector Institute researchers, attend cutting-edge ML meetups and conferences.
Greenfield innovation with enterprise backing: Build net-new ML systems from scratch with the freedom to experiment boldly, fail fast, and push boundaries.
Solve sophisticated ML challenges: Tackle hard problems at the intersection of NLP, document intelligence, reasoning systems, agentic workflows, and production-scale deployment.
Clear growth trajectory: High visibility to senior leadership, mentorship from experienced ML architects, and clear paths to Lead ML Engineer or Principal ML Engineer roles.
We'll Count on You To:
- Design and build transformative ML systems.
- Drive AI innovation through hands-on technical work.
- Lead projects and drive technical excellence.
- Mentor and elevate junior engineers.
- Build production ML infrastructure.
- Champion ML governance and operational excellence.
- Collaborate across teams effectively.
- Stay at the bleeding edge.
What You Need to Have:
- Strong ML engineering expertise – 6+ years of professional experience building production AI/ML systems.
- Advanced generative AI and LLM experience.
- Deep ML technical skills – Strong proficiency in Python and ML algorithms.
- Bachelor's degree in Machine Learning, Computer Science, Data Science, Applied Mathematics, or related field.
- Production ML engineering excellence.
- Software development fundamentals.
- Technical leadership through influence.
- Outstanding collaboration and communication.
What Would Make You Stand Out:
- Cutting-edge AI implementation experience.
- Multi-agent and agentic systems expertise.
- MLOps and cloud-native infrastructure.
- Document and content management systems experience.
- Technical thought leadership.
- Financial services or analytical domain knowledge.
- Startup or innovation environment experience.
- Toronto AI/ML community involvement.
If you're ready to build transformative ML systems with organizational backing, cutting-edge technology, and talented colleagues—this is the moment to join us.
Senior MLOps and Machine Learning Engineer in London employer: Fitch Ratings
Fitch Solutions is an exceptional employer, offering a vibrant work culture that prioritises collaboration and innovation within the financial services sector. With a strong commitment to employee growth through dedicated training and mentorship programmes, as well as a hybrid work environment that promotes work-life balance, Fitch empowers its team members to thrive and make a meaningful impact in their roles. Located in London, employees benefit from a dynamic city atmosphere while enjoying comprehensive health and wellness offerings, generous parental leave policies, and opportunities for community engagement.
StudySmarter Expert Advice🤫
We think this is how you could land Senior MLOps and Machine Learning Engineer in London
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Senior MLOps and Machine Learning Engineer in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Fitch Ratings, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Fitch Ratings. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Fitch Ratings
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Fitch Ratings!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
