Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Lead Machine Learning Engineer, Associate Director, London

Fitch Group
London
4 months ago
Applications closed

Related Jobs

View all jobs

KTP Associate: Machine Learning Engineer - Process Simulations

Lead AI/Machine Learning Engineer

Data Scientist

Data Scientist

Staff Data Scientist - Fraud

Senior Data Scientist

Fitch Group is currently seeking a Lead Machine Learning Engineer, Associate Director based out of our London office.

As a leading, global financial information services provider, Fitch Group delivers vital credit and risk insights, robust data, and dynamic tools to champion more efficient, transparent financial markets. With over 100 years of experience and colleagues in over 30 countries, Fitch Group's culture of credibility, independence, and transparency is embedded throughout its structure, which includes Fitch Ratings, one of the world's top three credit ratings agencies, and Fitch Solutions, a leading provider of insights, data and analytics. With dual headquarters in London and New York, Fitch Group is owned by Hearst.

About the Team

The Fitch Group's AI Implementation Chapter is seeking a dynamic Lead Machine Learning Engineer with 6+ years of experience, including leadership and people management. This role involves designing AI/ML solutions and ensuring implementation of AI initiatives across the Fitch Ratings organization. You will manage a team of 2-3 engineers, blending hands-on technical work with leadership responsibilities, while collaborating with product squads, business partners, and cross-functional teams to integrate advanced AI solutions into flagship Fitch Ratings products and workflows.

The AI Chapter's team objectives:

  • Implement AI & ML technology in collaboration with Fitch Ratings business partners and product squads
  • Develop and support enterprise-level AI exploration tools and capabilities
  • Provide guidance for efficient and secure development and deployment of AI
  • Establish and maintain guidelines and processes for AI/ML governance

How You'll Make an Impact:

  • Lead and manage a team of 2-3 machine learning engineers, balancing direct leadership with technical contributions to projects
  • Oversee the design, development, and deployment of scalable AI/ML solutions, focusing on advanced generative AI frameworks, large language models, and agentic workflows
  • Mentor and develop junior engineers, ensuring best practices in coding, architectural design, and project execution
  • Drive projects and strategic initiatives, ensuring the integration of ML solutions into existing workflows by collaborating with product squads and business stakeholders
  • Develop robust, production-quality software artifacts using Python and large-scale data workflow orchestration platforms (e.g., Airflow), while managing team resources & timelines
  • Leverage expertise in cloud computing platforms (AWS and Azure) to build and optimize AI infrastructure
  • Champion ML governance, ensuring adherence to guidelines, monitoring SLAs, and enhancing AI solutions' performance and reliability
  • Translate complex data science and ML concepts for technical and non-technical audiences, fostering alignment across distributed teams
  • Design and develop APIs (e.g. using FastAPI) for integration and deployment of ML models and solutions.

You May be a Good Fit if:

  • 6+ years of professional experience as an AI/ML engineer, with a strong record of delivering production-quality solutions.
  • Experience managing and mentoring technical teams, with the ability to lead people and technical strategy.
  • Extensive experience in developing and integrating advanced generative AI and ML solutions into existing products and systems.
  • Proficiency in Python and strong knowledge of ML algorithms, ranging from classical techniques to deep learning methods.
  • Experience in training, fine-tuning, and deploying neural network models using frameworks like PyTorch.
  • Expertise in containerization (e.g., Docker, Kubernetes, AWS EKS) and building scalable systems in cloud environments.
  • Deep understanding of software development fundamentals, including automated testing, source version control, and code optimization.
  • Excellent communication and collaboration skills, with the ability to interact effectively with both technical teams and business stakeholders.
  • Bachelor's degree in machine learning, computer science, data science, applied mathematics, or a related field (Master's or higher is strongly preferred).

What Would Make You Stand Out:

  • A track record of successfully leading project initiatives and shaping technical strategies through effective team management.
  • Familiarity with credit ratings agencies, industry regulations, and financial data products.
  • Experience developing/integrating functionality for Document and Content Management Systems.
  • Ability to support prototyping teams for seamless transitions from prototype to development and deployment.
  • Passion for leveraging data and ML to drive meaningful business outcomes while fostering a collaborative team environment.
  • Proven ability to integrate AI solutions into broader workflows and projects through cross-functional team collaboration

Why Choose Fitch:

  • Hybrid Work Environment:2 to 3 days a week in office required based on your line of business and location
  • A Culture of Learning & Mobility:Dedicated trainings, leadership development and mentorship programs designed to ensure that your time at Fitch will be a continuous learning opportunity
  • Investing in Your Future:Retirement planning and tuition reimbursement programs that empower you to achieve your short and long-term goals
  • Promoting Health & Wellbeing:Comprehensive healthcare offerings that enable physical, mental, financial, social, and occupational wellbeing
  • Supportive Parenting Policies:Family-friendly policies, including a generous global parental leave plan, designed to help you balance career and family life effectively
  • Inclusive Work Environment: A collaborative workplace where all voices are valued, with Employee Resource Groups that unite and empower our colleagues around the globe
  • Dedication to Giving Back:Paid volunteer days, matched funding for donations and ample opportunities to volunteer in your community

Fitch is committed to providing global securities markets with objective, timely, independent and forward-looking credit opinions. To protect Fitch's credibility and reputation, our employees must take every precaution to avoid conflicts of interest or any appearance of a conflict of interest. Should you be successful in the recruitment process at Fitch Ratings you will be asked to declare any securities holdings and other potential conflicts prior to commencing employment. If you, or your immediate family, have any holdings that may conflict with your work responsibilities, you may be asked to divest yourself of them before beginning work.

Fitch is proud to be an Equal Opportunity and Affirmative Action Employer. We evaluate qualified applicants without regard to race, color, national origin, religion, sex, sexual orientation, gender identity, disability, protected veteran status, and other statuses protected by law.

#LI-Hybrid

#LI-Group

#LI-JO
#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.

AI Team Structures Explained: Who Does What in a Modern AI Department

Artificial Intelligence (AI) and Machine Learning (ML) are no longer confined to research labs and tech giants. In the UK, organisations from healthcare and finance to retail and logistics are adopting AI to solve problems, automate processes, and create new products. With this growth comes the need for well-structured teams. But what does an AI department actually look like? Who does what? And how do all the moving parts come together to deliver business value? In this guide, we’ll explain modern AI team structures, break down the responsibilities of each role, explore how teams differ in startups versus enterprises, and highlight what UK employers are looking for. Whether you’re an applicant or an employer, this article will help you understand the anatomy of a successful AI department.