At a Glance
- Tasks: Join our team to develop and support cutting-edge AI and ML solutions.
- Company: Fitch Group is a global leader in financial information services with over 100 years of experience.
- Benefits: Enjoy hybrid work, comprehensive healthcare, tuition reimbursement, and generous parental leave.
- Why this job: Be part of a dynamic team driving innovation in AI while making a real impact.
- Qualifications: 3+ years in AI/ML engineering, strong coding skills, and a relevant degree required.
- Other info: Recognised as a top tech workplace for three consecutive years.
The predicted salary is between 42000 - 84000 ÂŁ per year.
Social network you want to login/join with: Machine Learning Engineer, London, London EU work permit required: Fitch Group is currently seeking a Machine Learning Engineer 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. Fitch\’s Technology & Data Team is a dynamic department where innovation meets impact. Our team includes the Chief Data Office, Chief Software Office, Chief Technology Office, Emerging Technology, Shared Technology Services, Technology, Risk and the Executive Program Management Office (EPMO).Driven by our investment in cutting-edge technologies like AI and cloud solutions, we’re home to a diverse range of roles and backgrounds united by a shared passion for leveraging modern technology to drive projects that matter to our organization and clients. We are also proud to be recognized by Built In as a “Best Place to Work in Technology” 3 years in a row. Want to learn more about a career in technology and data at Fitch? The Fitch Group’s AI Implementation Chapter is seeking a Machine Learning Engineer to be part of a team dedicated to building and supporting Generative AI, Machine Learning (ML) and Data Science solutions across the Fitch Ratings organization. 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 Work closely with or as part of product squads to build, integrate, and deploy AI and ML solutions, sharing best practices and learnings with other squad members. Effectively communicate data science & ML concepts to stakeholders, focusing on applicability to Fitch use cases Collaborate in developing and deploying ML & Gen AI solutions to meet enterprise goals and support innovation and experimentation. Collaborate with data scientists to identify innovative solutions that leverage data to meet business objectives. Develop, in collaboration with senior engineers, scalable solutions and workflows that leverage ML & Gen AI to meet enterprise requirements. Support production applications by helping maintain SLAs, using metrics to evaluate and guide the improvement of existing ML solutions Use AWS and Azure cloud services to provide the necessary infrastructure, resources, and interfaces for data loading and LLM workflows. Use Python and large-scale data workflow orchestration platforms ( Airflow) to build software artifacts for ETL, integrating diverse data formats and storage technologies, and incorporate them into robust data workflows and dynamic systems 3+ years of work experience as an AI/ML engineer ~ Strong adherence to software and ML development fundamentals (, code quality considerations, automated testing, source version control, optimization) • Experience in integrating AI solutions into existing workflows ~ Experience building Generative AI frameworks, leveraging and/or finetuning LLMs. (experience building agentic workflows strongly preferred) ~ Experience building/enhancing search and information retrieval systems ~ Exposure/experience in containerization technologies like docker, Kubernetes, AWS EKS etc. ~ Proficiency in ML algorithms, such as multi-class classification, decision trees, support vector machines, and neural networks (deep learning experience strongly preferred) ~ Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services , AWS Bedrock, S3, SageMaker; Azure AI Search, OpenAI, blob storage, etc. • Bachelor’s degree (master’s or higher strongly preferred) in machine learning, computer science, data science, applied mathematics or related technical field Experience developing/integrating functionality for/in Document Management Systems and content management systems Experience supporting prototyping teams to enable seamless transition from prototype to development and deployment Experience building agentic workflows powered by language models Passion for using data and ML to drive better business outcomes for customers Proven ability to collaborate with non-AI/ML teams to integrate AI solutions into broader workflows and projects. Familiarity with credit ratings agencies, regulations, and data products Excellent written and verbal communication skills • Advocate of good code quality and architectural practices Hybrid Work Environment: 2 to 3 days a week in office required based on your line of business and location Dedicated trainings, leadership development and mentorship programs designed to ensure that your time at Fitch will be a continuous learning opportunity Retirement planning and tuition reimbursement programs that empower you to achieve your short and long-term goals 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 Dedication to Giving Back: Paid volunteer days, matched funding for donations and ample opportunities to volunteer in your community 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. We evaluatequalified applicants without regard to race, color, national origin, religion, sex, sexual orientation, gender identity, disability, protected veteran status, and other statuses protected by law. #
Machine Learning Engineer - Artificial Intelligence employer: Fitch Ratings
Contact Detail:
Fitch Ratings Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer - Artificial Intelligence
✨Tip Number 1
Familiarise yourself with Fitch Group's core values and mission. Understanding their commitment to transparency and innovation will help you align your responses during interviews, showcasing how your personal values resonate with theirs.
✨Tip Number 2
Network with current employees or alumni who work at Fitch Group. Engaging in conversations about their experiences can provide valuable insights into the company culture and expectations, which you can leverage during your application process.
✨Tip Number 3
Stay updated on the latest trends in AI and machine learning, particularly in the financial sector. Being able to discuss recent advancements or case studies during interviews will demonstrate your passion and expertise in the field.
✨Tip Number 4
Prepare to discuss specific projects where you've successfully integrated AI solutions into existing workflows. Highlighting your hands-on experience will show your capability to contribute effectively to Fitch Group's objectives.
We think you need these skills to ace Machine Learning Engineer - Artificial Intelligence
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning and AI. Focus on projects where you've implemented ML algorithms, built generative AI frameworks, or worked with cloud services like AWS and Azure.
Craft a Compelling Cover Letter: In your cover letter, express your passion for using data and ML to drive business outcomes. Mention specific examples of how you've collaborated with teams to integrate AI solutions into workflows, showcasing your communication skills.
Showcase Technical Skills: Clearly list your technical skills related to the job description, such as proficiency in Python, experience with containerization technologies, and knowledge of ML algorithms. This will help demonstrate your fit for the role.
Highlight Continuous Learning: Mention any relevant training, certifications, or courses you've completed in AI and ML. This shows your commitment to staying updated in the field and aligns with Fitch Group's dedication to continuous learning.
How to prepare for a job interview at Fitch Ratings
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning algorithms, cloud services like AWS and Azure, and programming languages such as Python. Bring examples of past projects where you successfully implemented AI solutions.
✨Understand the Company’s Culture
Fitch Group values credibility, independence, and transparency. Familiarise yourself with their mission and how your role as a Machine Learning Engineer can contribute to these values. This will help you align your answers with their expectations.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about how you would approach integrating AI solutions into existing workflows or developing scalable ML solutions, and be ready to articulate your thought process.
✨Communicate Clearly and Effectively
Since you'll need to explain complex data science concepts to non-technical stakeholders, practice simplifying your explanations. Use clear language and avoid jargon to ensure your ideas are easily understood.