Staff ML Engineer: Lead Architect, Production ML Systems

Global Sports Jobs Limited; Phoenix (AZ); On-site; USD 180,000 - 250,000; Full time

Benefits offered by this job

A Great Place to work.

Fast track growth opportunities.

Thoughtfully curated benefits.

Tools to explore and grow.

Job summary

Warner Bros. Discovery is seeking a Staff Machine Learning Engineer to set the technical direction for the Hyderabad ML Engineering team within the Data & Audience Platform.

You will own architecture for identity and audience intelligence, forecasting, and MLOps, partnering with senior leaders to guide multiple workstreams. You will drive standardisation of ML practices, lead the delivery of scalable, monitored ML systems, and influence decisions across organizational boundaries.

Qualifications

• 8+ years of ML engineering with staff-level scope.

Responsibilities

• Define and own the technical architecture for core ML systems.
• Lead MLOps framework decisions across training, serving, and monitoring.
• Evaluate and adopt new technologies with buy/build/partner assessments.
• Standardise ML practices across teams and align with global standards.
• Architect and deliver probabilistic identity resolution and real-time ML workflows.
• Lead evolution of Audience Intelligence and forecasting models.
• Ensure production-grade, monitored models with continuous improvement.
• Define MLOps target architecture and governance for full lifecycle.

Skills

ML engineering

Staff leadership

Communication

Influence across teams

Production monitoring

Education

Master's or Ph.D. in CS/Stats/ML

Tools

Databricks

Delta Lake

Unity Catalog

MLflow

SageMaker

Snowflake

Graph ML

LangGraph

CrewAI

Job description

Warner Bros. Discovery is seeking a Staff Machine Learning Engineer to set the technical direction for the Hyderabad ML Engineering team within the Data & Audience Platform.

You will own architecture for identity and audience intelligence, forecasting, and MLOps, partnering with senior leaders to guide multiple workstreams. You will drive standardisation of ML practices, lead the delivery of scalable, monitored ML systems, and influence decisions across organizational boundaries.