below marketmost similar roles pay hereabove market
This role pays more than
55%
of similar roles. Most pay
$211,612–$270,500
— the blue band above.
At the midpoint, this role pays about
$246k
versus about
$241k
for comparable roles.
Based on 240 similar postings.
Employer
About The Walt Disney Company
The Walt Disney Company is a diversified global entertainment and media enterprise operating in segments including Disney Parks, Experiences and Products; Entertainment (ABC, Hulu, Disney+); and ESPN. Industry: Entertainment & Media
The Walt Disney Company currently has
90 open roles
on FindRole.
Listed pay typically runs
$150,900–$202,400
across 90 roles with salary data.
The Senior Machine Learning Engineering Manager, Ad Platforms joins the Ad Platforms organization within Disney Entertainment and ESPN Technology. This leadership role involves managing data scientists, machine learning engineers, and AI engineers to build, enhance, and maintain a high-performance, distributed, microservice-based advertising platform. You will lead the design and deployment of scalable, maintainable models and pipelines, overseeing the end-to-end machine learning workflow from data collection to production. Key responsibilities include defining strategic directions for machine learning projects, mentoring senior contributors, and ensuring responsible AI practices. Required technical skills include proficiency in Python, Java, and frameworks like TensorFlow, PyTorch, JAX, and Hugging Face. You will solve complex problems in ad serving, delivery, and campaign management using MLOps practices and cloud platforms to power video advertising across various online properties.
Lead and mentor senior data scientists and machine learning engineers to build scalable, high-impact AI solutions.
Define the strategic direction for machine learning projects in collaboration with product and engineering stakeholders.
Oversee the end-to-end machine learning workflow, including data collection, model development, and production deployment.
Drive the adoption of industry best practices for model development, code quality, testing, and documentation.
Translate business requirements into well-defined technical implementations and define operational metrics to measure system health.
Ensure responsible AI practices by maintaining standards for fairness, explainability, and privacy compliance.
Explore and implement new ML techniques, tools, and technologies to foster innovation within the Ad Platform.
Participate in on-call rotations to support ML/AI solutions based on the team's escalation policy.
What we're looking for
Bachelor’s or master’s degree in computer science, Engineering, Mathematics, Statistics, or a related field.
10+ years of relevant industry experience.
At least 5 years of experience in people-management managing senior ICs and managers.
Proven ability to translate business problems into scalable ML and GenAI solutions with strong understanding of ML fundamentals, deep learning, and statistical modeling.
Proven experience designing, building, and deploying scalable machine learning models and systems in production.
Experience deploying ML/GenAI systems at scale using cloud platforms and MLOps practices.
Advanced programming proficiency in Python, Java, or similar, and experience with ML/DL frameworks like TensorFlow, PyTorch, JAX, or Hugging Face.
Experience building, fine-tuning, evaluating, and deploying LLM-based systems including RAG, prompt engineering, and model optimization.
Demonstrated ability to lead global teams and collaborate across organizational boundaries.
Domain knowledge in the Ad Tech industry (preferred).
Experience working with large-scale data and distributed systems (preferred).
Knowledge of cloud platforms and MLOps pipelines (preferred).
Track record of innovation and contributions to the ML/AI community (preferred).
Machine Learning
Python
Java
Reinforcement Learning
Spark
Hadoop
Quantitative Optimization
Control Theory
Distributed Frameworks
Design of Experiments
Statistics
Forecasting
Agile
Production Systems
Machine Learning
Python
Java
Reinforcement Learning
Spark
Hadoop
Optimization
Control Theory
Statistics
Distributed Frameworks
Agile
Design of Experiments
Production Systems
Forecasting
Remote (New York, NY)63 days ago
$292,500–$409,500
Machine Learning Systems
Distributed Systems
ML Platforms
Spark
Flink
Kafka
Ray
Airflow
Iceberg
Kubernetes
BigQuery
Snowflake
Databricks
Data Pipelines
Streaming Computation
Observability
Python
Java
C++
PyTorch
TensorFlow
XGBoost
Large Language Models
Deep Learning
Natural Language Processing
Retrieval-Augmented Generation
RAG
Sequence Modeling
Information Retrieval
Recommendation Systems
A/B Testing
Feature Engineering
Prompt Engineering