Lead Machine Learning Engineer

Disney Entertainment Television is seeking a Lead Machine Learning Engineer to join its New York, NY onsite team. This senior individual contributor will provide technical leadership for complex ML systems and the data foundations required to operate them, applying scalable machine learning techniques to identity, audience, and cross-platform measurement. The role involves shaping architecture and standards for end-to-end ML pipelines that capture, manage, and utilize large-scale structured and unstructured data across Snowflake and Databricks, with a salary range of USD 179,700 to 225,000 per year.

Responsibilities

• Lead the development, training, and deployment of advanced ML models for identity resolution, look-alike modeling, and cross-platform measurement; translate algorithms into production-quality code and optimize for scale and performance.
• Architect scalable ML platforms and reusable components, including training/inference pipelines, feature/label foundations, and model serving patterns across distributed cloud and platform environments.
• Lead data and feature foundations by defining data contracts, metadata and lineage expectations, and automated quality controls to maintain data integrity across structured and unstructured sources in Snowflake and Databricks.
• Establish MLOps and reliability practices with CI/CD patterns, model versioning/registry, automated evaluation, drift detection, monitoring dashboards and alerts, and operational playbooks for sustained production health.
• Provide cross-functional technical leadership, driving design reviews, clarifying requirements, and guiding multi-quarter initiatives with product, analytics, and platform engineering stakeholders.
• Mentor engineers through code and design reviews, and build shared libraries and best practices to improve team velocity and quality.
• Ensure privacy, governance, and compliance through privacy-by-design, PII safeguards, documentation, and audit readiness across ML workflows (GDPR/CCPA).

Requirements

• Strong production experience with deep-learning, generative AI, or retrieval-augmented systems (PyTorch, vector databases) and real-time data pipelines (Kafka, Pub/Sub, Kinesis).
• 7+ years of professional experience delivering production ML systems (models, pipelines, and monitoring) at scale.
• Advanced coding skills in Python and SQL, with a strong software engineering discipline (testing, CI/CD, code reviews, design documentation).
• Proven ability to apply ML techniques to develop predictive systems at scale, including deep learning where appropriate.
• Hands-on expertise with cloud-native data platforms and distributed compute (Snowflake/Databricks/Spark/BigQuery) and container orchestration (Docker/Kubernetes).
• Demonstrated ability to lead technical initiatives across teams and influence architecture and standards.
• 8+ years of total experience, with hands-on work in media, advertising technology, or cross-platform audience measurement.
• Strong understanding of modern MLOps stacks (MLflow, Kubeflow, Vertex AI, SageMaker) and model governance practices (metadata, lineage, drift detection).
• Certifications such as Google Professional Machine Learning Engineer, AWS Certified Machine Learning – Specialty, or equivalent cloud/data credentials.
• Contributions to open-source ML or data-engineering projects, conference presentations, or peer-reviewed publications.
• Experience in media/ad tech, identity graphs, audience measurement, or interoperability layers.
• Bachelor’s degree in a relevant technical or science field; Master’s degree or PhD in a related discipline is also noted.

Technologies

• PyTorch
• Vector databases
• Kafka
• Pub/Sub
• Kinesis
• Snowflake
• Databricks
• Spark
• BigQuery
• Docker
• Kubernetes
• MLflow
• Kubeflow
• Vertex AI
• SageMaker
• Python
• SQL

Benefits

• Medical benefits
• Financial benefits
• Bonus and/or long-term incentive units

Department / Group Overview

The cross-media measurement and advanced analytics organization handles data strategy and management, cross-platform content measurement, content marketing measurement, and linear and digital inventory forecasting. The team delivers advanced analytics and actionable insights related to Disney entertainment content, monetization, and audience development. The Data and Analytics Operations team is part of the Cross-Media group, CMMAA: Measurement and Advanced Analytics, which leverages advanced machine learning to provide a robust analytics suite, including descriptive, predictive, and prescriptive capabilities underpinned by strong data management and an interoperability layer to support business goals such as content production and marketing.