Lead Machine Learning Engineer (Remote)

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Requirements:

• 5+ years of experience in machine learning.
• Deep experience with current-generation ML algorithms and frameworks (e.g., XGBoost, PyTorch, TensorFlow).
• 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).
• Experience with cloud platforms like AWS SageMaker, Databricks, GCP, Snowflake, or Azure.
• Experience in 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.

Responsibilities:

• Develop and operationalize machine learning models by designing, building, and deploying scalable ML frameworks and pipelines.
• Lead the development of custom models, including LLMs and traditional ML algorithms for applications such as credit risk, fraud detection, and customer insights.
• Shape Experian's AI Platform by overseeing the creation of tools for training, fine-tuning, and deploying models, including generative AI applications.
• Ensure robust system architecture for managing high-volume data and model evaluations.
• Mentor a diverse team and work with stakeholders to align technical solutions with business goals.
• Handle challenges related to model bias, fairness, and explainability while establishing best practices for development.