[Hiring] ML Engineer

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Role Description

This role involves contributing to a team responsible for developing machine learning (ML) algorithms, models, and data pipelines for digital and linear advertising. • Use Keras, TensorFlow, PyTorch, Spark, Python, and Scala within an Agile development environment • Deploy ML models using AWS services, including EMR and Sagemaker • Ensure ML model governance and measure ML model drifts using Python and MLFlow • Build and maintain CI/CD pipelines for ML use cases using Concourse, Github, and Terraform • Use the Databricks platform for data analytics • Create feature stores using Databricks features including Feature Store, Delta Tables, and Online Table Store • Identify data drift and model degradation over time and create necessary alerts to proactively address issues with deployed models • Collaborate with data engineers, data scientists, and technical leads to develop and deliver cloud-based solutions to support scalable and reliable data science workflows • Partner with Data Engineering to produce data pipelines • Implement a robust system for measuring and optimizing the quality of deployed algorithms and models • Design and implement enterprise ML Ops • Collaborate with data scientists to help integrate ML Ops into the model development process • Assist in setting best practices to support scalable data science solutions

Position is eligible for 100% remote work.