Lead Machine Learning Engineer

Summary

Join Experian's Technology, Software Solutions, and Innovation (TSSI) team as a Lead Machine Learning Engineer. Lead the development of Experian's AI platform and machine learning models, including cutting-edge solutions leveraging generative AI. You will design scalable ML solutions, develop advanced pipelines, and deliver impactful models. Collaborate with a team of engineers and scientists, mentor junior team members, and work with stakeholders to align technical solutions with business goals. This role requires significant experience with ML algorithms, frameworks, and programming languages, as well as experience building and maintaining large-scale ML systems. Experian offers a competitive compensation package, core benefits, and a flexible work environment.

Requirements

• 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

Responsibilities

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

Preferred Qualifications

Domain expertise in financial services, credit modeling, or healthcare analytics

Benefits

• Great compensation package and bonus plan
• Core benefits, including medical, dental, vision, and matching 401K
• Flexible work environment, ability to work remotely, hybrid, or in-office
• Flexible time off, including volunteer time off, vacation, sick, and 12-paid holidays