Director of Machine Learning Engineering - Shaping the Future of AI at Experian through Innovative Engineering Leadership - US REMOTE ONLY

Remote Full-time
Unlocking the Power of Data with Experian's Experian Software Solutions Team

At Experian, we're not just a company; we're a catalyst for change, leveraging the power of data to transform lives and create opportunities for consumers, businesses, and society. With a rich history spanning over 125 years, we've established ourselves as a leader in the industry, and our commitment to innovation has earned us a spot among FORTUNE's 100 Best Companies to Work For and Forbes' 100 World's Most Innovative Companies.

Our Experian Software Solutions (ESS) team is at the forefront of this innovation, bringing together data, technology, and data science to build game-changing products and services for our clients. We're now seeking a Director of Machine Learning Engineering to lead the development of our AI platform and products, driving our mission to increase the rigor and scalability of our modeling approach, tackle critical issues like bias and fairness, and adapt to the evolving landscape of generative AI.

Job Overview

As the Director of Machine Learning Engineering, you'll be part of a dynamic team that's shaping the future of AI at Experian. You'll lead a diverse team of engineers and scientists responsible for developing and operationalizing our machine learning platform, defining and shaping our tech culture, and contributing to the development of our products and software architecture.

Key Responsibilities:


Lead a diverse development team to build and maintain a scalable development framework for rapid development, evaluation, and deployment of custom machine learning models, including large language models (LLMs).
Oversee the build of ambitious client-facing applied AI models, leveraging generative AI, through to production release.
Design and develop complex frameworks for applying ML/data science techniques to large structured and unstructured data volumes.
Develop scalable pipelines, tools, and services for building production-ready machine learning models.
Determine the best implementation approaches for technically complex features to inform product roadmaps.
Work closely with product owners and end-users to pilot products.
Establish a culture of developing high-quality models and software through rapid data-driven decision making, automation, and streamlined processes.
Set design principles, coding standards, and development practices for your team and others in the organization working on adjacent applications.


Qualifications and Skills

To succeed in this role, you'll need a strong foundation in machine learning engineering and/or data science, with a passion for leadership and innovation. Here are the essential qualifications and skills we're looking for:

Essential Qualifications:


Bachelor's degree in Computer Science, Engineering, Statistics, or a related field.
8+ years of industry experience as a hands-on practitioner of machine learning engineering and/or data science, including 2+ years in leadership roles managing teams.
Deep experience with current-generation data science algorithms and processes, including modern language models (e.g., Transformers) and generative AI models (e.g., fine-tuning, prompt engineering of GPT APIs, reinforcement learning).
Expert knowledge in Python (e.g., pandas, numpy, sklearn, pytorch, langchain), SparkSQL, and data science platforms such as AWS Sagemaker or Databricks.
Track record of building and maintaining large-scale machine learning and/or data engineering systems in production.


Preferred Qualifications:


Familiarity with writing asynchronous REST API backends.
Familiarity with data-oriented workflow orchestration frameworks (e.g., Kubernetes), DevOps tooling, including Jenkins, ArgoCD, and common cloud infrastructure (e.g., AWS suite).
Comfortable supporting troubleshooting and triage of production issues when needed.
Strong test writing discipline and confident in standard development tools and processes (e.g., git, Jira, Slack).
Experience in financial services and/or credit modeling and/or healthcare analytics.


What We Offer

At Experian, we believe in creating a thriving, inclusive, and diverse team where people love their work and love working together. Here are some of the benefits and perks you can expect:


A competitive base salary and variable pay opportunity.
A comprehensive benefits package, including health, life, and disability insurance, generous paid time off, and parental and family care leave.
An employee stock purchase plan and a 401(k) plan with a company match.
Opportunities for career growth and professional development.
A culture that values diversity, equity, and inclusion, and celebrates the uniqueness of every individual.


Why Join Us?

By joining our team, you'll be part of a dynamic and innovative organization that's shaping the future of AI and data science. You'll have the opportunity to work on complex and challenging projects, collaborate with talented professionals, and contribute to the development of cutting-edge technologies.

We're committed to creating a work environment that's inclusive, supportive, and empowering. Our culture is built on the principles of diversity, equity, and inclusion, and we're dedicated to making a positive impact on our employees, customers, and the wider community.

Ready to Apply?

If you're a motivated and talented individual ready to contribute to a thriving team, we encourage you to apply now! We're excited to review your application and discuss how you can help shape the future of AI at Experian.

Experian is an Equal Opportunity and Affirmative Action employer. We welcome applications from diverse candidates and are committed to creating a workplace that's inclusive and respectful of all individuals.

Apply Now

Apply Now

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