Full-Time Lead Machine Learning Engineer

The Technology, Software Solutions, and Innovation (TSSI) team is at the forefront of combining data, technology, and data science to create transformative products and services for our clients.

As a Lead Machine Learning Engineer, you will lead the development of Experian's AI platform and machine learning models, including cutting-edge solutions leveraging generative AI (GenAI).

This is a unique opportunity to shape the future of AI-driven products, addressing challenges such as model scalability, fairness, and explainability.

You will work with a team of engineers and scientists to design scalable ML solutions, develop advanced pipelines, and deliver impactful models for real-world applications.

Beyond technical contributions, you'll help define Experian's technical culture, establish best practices, and drive innovation across our AI initiatives.

You will report to the Director of Machine Learning Engineering.

Your responsibilities include:

1. Develop and Operationalize Machine Learning Models: Design, build, and deploy scalable ML frameworks and pipelines to support structured and unstructured data use cases.
2. Lead the development of custom models, including LLMs and traditional ML algorithms, for credit risk, fraud detection, and customer insights.
3. Shape Experian's AI Platform: Oversee the creation of advanced tools and services for training, fine-tuning, and deploying models, including generative AI applications.
4. Ensure robust system architecture to handle high-volume data and rigorous model evaluations.
5. Leadership and Collaboration: Mentor a diverse team of engineers and scientists, setting standards for high-quality development.
6. Work with product managers, end-users, and stakeholders to align technical solutions with the business goals.
7. Advance AI Excellence: Handle challenges such as model bias, fairness, and explainability.
8. Establish best practices for model development, automation, and streamlined processes to deliver reliable, production-ready AI systems.

Your background should include:

• 5+ years of experience
• Deep experience with current-generation ML algorithms and frameworks (e.g., XGBoost, PyTorch, Tensorflow) and hands-on expertise with generative AI (e.g., fine-tuning GPT, reinforcement learning).
• Programming skills in Python (e.g., Pandas, NumPy, PyTorch, LlamaIndex, Langchain, Haystack) and experience with platforms like AWS SageMaker, Databricks, GCP, Snowflake or Azure.
• Experience building and maintaining large-scale ML systems in production, including data pipelines and orchestration tools (e.g., Kubernetes, Jenkins).
• Experience with asynchronous REST API development, cloud infrastructure, and DevOps practices.
• Familiarity with testing, troubleshooting, and triaging production issues.
• Domain expertise in financial services, credit modeling, or healthcare analytics is a plus.

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