Machine Learning Engineer - GenAI

Job Description

The Generative AI Centre of Expertise (GenAI CoE) at Experian exists to improve our products, our internal processes and our day-to-day work through GenAI and process automation.  The team is a mix of ML engineers, data scientists and product owners, who are dedicated to the next wave of innovation using GenAI. 

Who is a ML Engineer?

In the GenAI CoE, ML Engineers drive the delivery of concepts and proven ideas into products and services that Experian can take to their customers, whether that be businesses or direct to consumers. To do this, we build upon the outcomes of our experiments to meet the product requirements - considering performance, maintainability, and scalability. We, alongside the data scientists in the team, collaborate with a range of stakeholders.

You will:

• Partner with teams across the organisation to design and build GenAI solutions—from early experimentation to full-scale production—potentially including DevOps work where needed.
• Architect and build high-performant solutions, which may involve traditional ML modelling and/or large datasets, as well as GenAI.
• Discover and introduce new technologies to the team, staying up to date with the latest approaches that enable the next generation of Experian’s products with GenAI and ML.
• Learn quickly and be able to put new GenAI concepts into practice.
• Spend 10% of your work time on continuous learning and sharing expertise on generative-AI technologies.

You

• Have experience in Python.
• Are a self-starter with strong troubleshooting skills.

It would be fantastic if you also have:

• Have a degree or equivalent qualification in a STEM subject.
• Are familiar with Unix environments.
• Exposure to at least one other programming language besides Python.
• Proficiency in object-oriented programming (OOP), SOLID principles, and test-driven development (TDD).
• Proficiency with Docker and experience working with container orchestration tools such as Kubernetes, Docker Swarm, or cloud-based alternatives.
• Comfort working across the full development stack, especially for prototyping.
• Passion for applying GenAI and machine learning across diverse domains and throughout the full project lifecycle.
• Conceptual understanding of common ML approaches (e.g., LLMs, GBMs, deep learning) and typical software architectures.
• Detailed-oriented, pragmatic, and collaborative team player.
• Experience as a lead developer tackling complex problems at scale.
• Experience mentoring junior engineers.
• Familiarity with various machine learning frameworks and toolkits (e.g., scikit-learn, XGBoost, TensorFlow).
• Hands-on experience building GenAI solutions using patterns such as Retrieval-Augmented Generation (RAG) or fine-tuning Large Language Models (LLMs).
• Have experience with cloud computing platforms.
• Greater familiarity with AWS compared to other cloud computing platforms.
• Have experience developing REST APIs.

Qualifications

• Python
• Self-starter with strong troubleshooting skills
• Machine learning

Additional Information

Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's people first approach is award-winning; World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ in 24 countries, and Glassdoor Best Places to Work 2024 to name a few. Check out Experian Life on social or our Careers Site to understand why.

Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

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