Overview
On Site
BASED ON EXPERIENCE
Full Time
Contract - Independent
Contract - W2
Contract - 4+ mo(s)
Skills
ML ENGINEER
Job Details
Job Description: THIS ROLE IS REMOTE
MAX BILL RATE: ***
Job Title: ML Engineer
Experience: 8 to 12 Yrs
Required Skills: Databricks, ML Ops, ML Flow, Databricks Workflows
Job Summary: Deep understanding of Databricks Workflows for automating model training, validation, deployment pipelines Proficiency in Databricks MLflow for tracking experiments, logging metrics, managing models through the entire lifecycle Experience with Databricks Model Registry, including registering,versioning,managing models for deployment in production environments Experience with model monitoring and logging to track performance, identify issues, ensure models are functioning as expected in production
Responsibilities: Knowledge of model versioning and rollback strategies, ensuring smooth transitions between model updates. Familiarity with data engineering concepts, such as ETL pipelines. Knowledge of MLOps best practices to facilitate model deployment, monitoring, and scalability in production environments. Collaboration skills for working cross-functionally with data scientists to ensure seamless model deployment and integration. The overarching goal of the Segmentation Team is to understand our customers (who they are, how they are watching, why they are watching, what they are watching) with the aim of reducing churn. The Segmentation team focuses on 1) Coordination with stakeholders (Content Strategy, Retention, Marketing, Merchandising) to answer specific business questions and optimize their targeting 2) Building models to better understand customers 3) Providing insights or analytics to drive business decisions. Will be working on Customer centric DS and ML models. Preferred time zone is 9 5 ET with CT and PT as the next choices.
Years of Experience: 12.00 Years of Experience
MAX BILL RATE: ***
Job Title: ML Engineer
Experience: 8 to 12 Yrs
Required Skills: Databricks, ML Ops, ML Flow, Databricks Workflows
Job Summary: Deep understanding of Databricks Workflows for automating model training, validation, deployment pipelines Proficiency in Databricks MLflow for tracking experiments, logging metrics, managing models through the entire lifecycle Experience with Databricks Model Registry, including registering,versioning,managing models for deployment in production environments Experience with model monitoring and logging to track performance, identify issues, ensure models are functioning as expected in production
Responsibilities: Knowledge of model versioning and rollback strategies, ensuring smooth transitions between model updates. Familiarity with data engineering concepts, such as ETL pipelines. Knowledge of MLOps best practices to facilitate model deployment, monitoring, and scalability in production environments. Collaboration skills for working cross-functionally with data scientists to ensure seamless model deployment and integration. The overarching goal of the Segmentation Team is to understand our customers (who they are, how they are watching, why they are watching, what they are watching) with the aim of reducing churn. The Segmentation team focuses on 1) Coordination with stakeholders (Content Strategy, Retention, Marketing, Merchandising) to answer specific business questions and optimize their targeting 2) Building models to better understand customers 3) Providing insights or analytics to drive business decisions. Will be working on Customer centric DS and ML models. Preferred time zone is 9 5 ET with CT and PT as the next choices.
Years of Experience: 12.00 Years of Experience
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