Distinguished Engineer - Machine Learning

Job Posting Title:Distinguished Engineer - Machine Learning

Req ID:10120854

Job Description:

About Disney Entertainment & ESPN Technology:

Disney Entertainment and ESPN Technology (DE&E Technology) provides the technological backbone and product development for Disney’s two media business units, while helping to keep the company at the vanguard of innovation – enabling the Company to continuously leverage technology to enhance storytelling and creativity, while delivering scalability, flexibility, and efficiency for its businesses.

Department Overview

On any given day at Disney Entertainment & ESPN Technology, we’re reimagining ways to create magical viewing experiences for the world’s most beloved stories while also transforming Disney’s media business for the future. Whether that’s evolving our streaming and digital products in new and immersive ways, powering worldwide advertising and distribution to maximize flexibility and efficiency, or delivering Disney’s unmatched entertainment and sports content, every day is a moment to make a difference to partners and to hundreds of millions of people around the world.

The Product Engineering team is responsible for end to end development for Disney’s world-class consumer-facing products, including streaming platforms Disney+, Hulu, and ESPN+, and digital products & experiences across ESPN, Marvel, Disney Studios, NatGeo, and ABC News. The team drives innovation at scale for hundreds of millions of consumers around the world across Apple, Android, Smart TVs, game consoles, and the web, with our platforms powering core experiences like personalization, search, messaging and data.

Job Summary

We are looking for a Distinguished Engineer - Machine Learning to design, architect and build a state of the art Recommendations system to power our personalized Discovery experiences across Disney+ and Hulu at scale. You will develop a deep understanding of our user and engagement data, and be a technical visionary and thought leader across the Recommendations systems and product development lifecycle to drive user Engagement. You will collaborate with, and influence Engineering, ML & Data Science, Product and Analytics teams.

If you are passionate about the customer experience and connecting the dots, and operating in a highly cross-functional collaborative team environment, this role is perfect for you!

Responsibilities

Develop a deep understanding of current ML models, algorithms and systems that power personalization and the metrics used to measure user engagement.

Analyze data to identify gaps/opportunities.

Propose/implement new ideas/models/algorithms for personalized recommendations in order to increase engagement.

Learn through iterative AB testing and architect/design the platform for global scale, while being cost effective.

Shape software engineering and architecture best practices and standards.

Create a culture of innovation, experimentation and impact.

Qualifications

Bachelor's degree in Computer Science, Information Systems, Software, Electrical, or Electronics Engineer, or comparable field of study, and/or equivalent work experience.

15+ years of relevant professional experience.

Experience building state of the art recommendations algorithms and systems for global consumer facing products - synthesizing rich experiences that span Data Science, Data Engineering, Machine Learning and Systems Engineering.

Excellent written and verbal communication skills, ability to simplify, synthesize and present complex constructs.

Ability to dive deep into technical components when needed, while keeping the overall systems architecture in mind.

Preferred Qualifications

Experience with ML frameworks (TensorFlow, PyTorch or similar).

Experience with applying Generative AI, LLMs.

Experience with Data Engineering practices and tools (ETL, Snowflake, Spark).

Experience with Python and Airflow (or similar).

The hiring range for this position in San Francisco is $298,200 to $399,900 per year. 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 & Data Engineering

Job Posting Primary Business:PDE - Engagement Experiences & Platforms

Primary Job Posting Category:Machine Learning

Employment Type:Full time

Primary City, State, Region, Postal Code:San Francisco, CA, USA

Alternate City, State, Region, Postal Code:

Date Posted:2025-05-12

10120854