Machine Learning Engineer

• Partner with product and business teams to define problems and translate them into data-driven solutions.
• Conduct exploratory data analysis (EDA) and extract actionable insights from structured and unstructured datasets.
• Develop, validate, and iterate on predictive models using techniques in supervised, unsupervised, and/or time series learning.
• Communicate modeling outcomes through clear visualizations and presentations to both technical and non-technical stakeholders.
• Build and maintain robust pipelines for model training, evaluation, and inference.
• Deploy machine learning models into production with attention to scalability, performance, and observability.
• Monitor model drift and performance over time and develop retraining and versioning strategies.
• Collaborate with software and data engineering teams to integrate ML solutions into end-user applications and internal systems.

Senior Lead AI/ML Engineer

Director Applied AI Engineering

Mid-Level AI/ML/NLP Engineer

Senior Manager – Data and AI Platform Activation

Manager – Gen AI Engineering

Senior Manager – AI Engineer