Senior Machine Learning Engineer
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The role
Lead the design and deployment of end-to-end ML model pipelines for marketing platforms at scale, delivering measurable business impact.
Define the technical ML strategy with robust model architectures, governance, testing standards, and incident response for production systems.
Implement infrastructure-as-code, CI/CD pipelines, and ML automation, focusing on model monitoring and drift detection.
Design and optimize ML workflows to balance cost and performance, automating training and deployment across teams.
Collaborate with Data Science, Data Engineering, Product, and Marketing to deliver scalable ML solutions and mentor junior engineers.
Requirements: MS/PhD in CS/AI/ML or related field; 8+ years building and deploying ML pipelines; expert in AWS SageMaker; Docker and Apache Airflow; Python with TensorFlow/PyTorch; CI/CD, model monitoring, and governance; Snowflake/Spark; strong collaboration and leadership.
Define the technical ML strategy with robust model architectures, governance, testing standards, and incident response for production systems.
Implement infrastructure-as-code, CI/CD pipelines, and ML automation, focusing on model monitoring and drift detection.
Design and optimize ML workflows to balance cost and performance, automating training and deployment across teams.
Collaborate with Data Science, Data Engineering, Product, and Marketing to deliver scalable ML solutions and mentor junior engineers.
Requirements: MS/PhD in CS/AI/ML or related field; 8+ years building and deploying ML pipelines; expert in AWS SageMaker; Docker and Apache Airflow; Python with TensorFlow/PyTorch; CI/CD, model monitoring, and governance; Snowflake/Spark; strong collaboration and leadership.
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