The Walt Disney Company Logo

The Walt Disney Company

Lead Machine Learning Engineer

Posted Yesterday
Be an Early Applicant
In-Office
Glendale, CA, USA
142K-199K Annually
Senior level
In-Office
Glendale, CA, USA
142K-199K Annually
Senior level
The Lead Machine Learning Engineer will develop algorithms for personalization and recommendations, optimize data processes, and collaborate with cross-functional teams to enhance user experiences.
The summary above was generated by AI

Job Posting Title:

Lead Machine Learning Engineer

Req ID:

10151720

Job Description:

Translation

Role Location: 

This is an on-site role requiring 4 days in-person at designated office location.

Disney Entertainment and ESPN Product & Technology

Technology is at the heart of Disney’s past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – all working to build and advance the technological backbone for Disney’s media business globally.

The team marries technology with creativity to build world-class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses. We are Storytellers and Innovators. Creators and Builders. Entertainers and Engineers. We work with every part of The Walt Disney Company’s media portfolio to advance the technological foundation and consumer media touch points serving millions of people around the world. 

Here are a few reasons why we think you’d love working here:

Building the future of Disney’s media: Our Technologists are designing and building the products and platforms that will power our media, advertising, and distribution businesses for years to come.

Reach, Scale & Impact: More than ever, Disney’s technology and products serve as a signature doorway for fans' connections with the company’s brands and stories. Disney+. Hulu. ESPN. ABC. ABC News…and many more. These products and brands – and the unmatched stories, storytellers, and events they carry – matter to millions of people globally. 

Innovation: We develop and implement groundbreaking products and techniques that shape industry norms, and solve complex and distinctive technical problems.

Product Engineering is a unified team responsible for the engineering of Disney Entertainment & ESPN digital and streaming products and platforms. This includes product engineering, media engineering, quality assurance, engineering behind personalization, commerce, lifecycle, and identity.

Job Summary:

Our team designs and builds models that directly shape the user experience – powering personalization and engagement across our Disney Streaming’s suite of streaming video apps, notably Disney+ and Hulu. With a strong product mindset and a focus on usability, we ensure every ML-driven product enhances how users discover, interact, and enjoy our experiences.

As a member of this team you will collaborate across Engineering, Product, and Data teams to apply machine learning methods to meet strategic product personalization goals, explore innovative, cutting edge techniques that can be applied to recommendations, and constantly seek ways to optimize operational processes.

This is an Individual Contributor role. You will be expected to lead recommendation and personalization algorithm research, development, and productionization for product areas, and to coordinate requirements and manage stakeholder expectations with Product, Engineering, and Editorial teams. As an IC, you will also be responsible for helping to set the roadmap for algorithmic work — not only for how to approach product requests for new recommendation features, but for helping to drive larger company objectives in the areas of personalization and recommendations.

Responsibilities and Duties of the Role:

  • Algorithm Development and Maintenance: Utilize cutting edge machine learning methods to develop algorithms for personalization, recommendation, and other predictive systems; maintain algorithms deployed to production and be the point person in explaining methodologies to technical and non-technical teams
  • Feature Engineering and Optimization: Develop and maintain ETL pipelines using orchestration tools such as Airflow and Jenkins; deploy scalable streaming and batch data pipelines to support petabyte scale datasets
  • Development Best Practices: Maintain existing and establish new algorithm development, testing, and deployment standards
  • Collaborate with product and business stakeholders: Identify and define new personalization opportunities and work with other data teams to improve how we do data collection, experimentation and analysis

Required Education, Experience/Skills/Training:

Basic Qualifications

  • 7+ years of experience developing machine learning models, performing large-scale data analysis, and/or data engineering experience
  • 5+ years writing production-level, scalable code (Python, SQL)
  • 3+ years of experience developing algorithms for deployment to production systems
  • Led complex projects and mentored team members
  • In-depth understanding of modern machine learning (e.g. deep learning methods), models, and their mathematical underpinnings
  • Experience deploying and maintaining pipelines and in engineering big-data solutions using technologies like Databricks, S3, and Spark
  • Ability to gauge the complexity of machine learning problems and a willingness to execute simple approaches for quick, effective solutions as appropriate
  • Strong written and verbal communication skills

Preferred Qualifications

  • MS or PhD in statistics, math, computer science, or related quantitative field
  • Production experience with developing content recommendation algorithms at scale
  • Experience building and deploying full stack ML pipelines: data extraction, data mining, model training, feature development, testing, and deployment
  • Familiar with metadata management, data lineage, and principles of data governance
  • Experience loading and querying cloud-hosted databases

Experience with:

  • AWS, Databricks

Required Education  

  • Bachelor’s Degree in Computer Science, Math, Statistics, or related quantitative field
The hiring range for this position in New York, NY is $148,700 - $199,400 per year and in Santa Monica, CA is $141,900 - $190,300. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

Job Posting Segment:

Product Engineering

Job Posting Primary Business:

PE - Streaming Backend

Primary Job Posting Category:

Software Engineer

Employment Type:

Full time

Primary City, State, Region, Postal Code:

Glendale, CA, USA

Alternate City, State, Region, Postal Code:

USA - NY - 7 Hudson Square

Date Posted:

2026-05-21

Similar Jobs

3 Days Ago
Hybrid
209K-286K Annually
Senior level
209K-286K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Lead the design and implementation of machine learning applications, mentor teams, ensure performance and scalability, and leverage cloud technologies.
Top Skills: AWSAzureGCPJavaPythonScala
8 Days Ago
Hybrid
230K-286K Annually
Senior level
230K-286K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
The role involves designing and developing machine learning applications, collaborating with Agile teams, optimizing ML systems, and ensuring high availability and performance of models.
Top Skills: AWSAzureDaskGoogle Cloud PlatformJavaPythonPyTorchScalaScikit-LearnSparkTensorFlow
Yesterday
In-Office
180K-225K Annually
Senior level
180K-225K Annually
Senior level
Digital Media • Gaming • News + Entertainment • Sports
The Lead Machine Learning Engineer will provide technical leadership in developing and deploying advanced ML models, ensuring data integrity, and mentoring engineers.
Top Skills: BigQueryDatabricksDockerKafkaKinesisKubeflowKubernetesMlflowPub/SubPythonPyTorchSagemakerSnowflakeSparkSQLVertex Ai

What you need to know about the Los Angeles Tech Scene

Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.

Key Facts About Los Angeles Tech

  • Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
  • Key Industries: Artificial intelligence, adtech, media, software, game development
  • Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
  • Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account