採用
福利厚生
•Healthcare
•401(k)
•Equity
必須スキル
Machine Learning
Python
Java
SQL
Deep Learning
Transformers
LLM
RAG
Job Posting Title:
Senior Machine Learning Engineer, Ads Research
Req ID:
10140854
Job Description:
Disney Entertainment & ESPN Technology
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.
A few reasons why we think you’d love working for Disney Entertainment & ESPN Technology
-
Building the future of Disney’s media business: DE&E Technologists are designing and building the infrastructure that will power Disney’s media, advertising, and distribution businesses for years to come.
-
Reach & Scale: The products and platforms this group builds and operates delight millions of consumers every minute of every day – from Disney+ and Hulu, to ABC News and Entertainment, to ESPN and ESPN+, and much more.
-
Innovation: We develop and execute groundbreaking products and techniques that shape industry norms and enhance how audiences experience sports, entertainment & news.
Ad Platforms organization within Disney Entertainment and ESPN Technology is fully responsible for building, enhancing and maintaining the high-performance, distributed, microservice-based Advertising Platform across all of Disney online properties, including Hulu and ESPN+. We build and maintain proprietary technology, ranging from ad serving and ad delivery, campaign management, reporting as well as all the integrations internal and external that come with evolving and maintaining a best-in-class video advertising business.
Our mission is to advance AI and machine learning capabilities across Ad Platform by delivering scalable, high impact AI/ML and data science solutions that enhance Ad decisioning, forecasting, experimentation and Ad experience. We are seeking a Lead Machine Learning Engineer to join this innovative team. This role offers a unique leadership opportunity for an experienced ML engineer who thrives at the intersection of technical excellence, strategic impact, and cross-functional collaboration.
WHAT YOU’LL DO
- Drive innovation and apply state of the art AI and machine learning across advertising domains, including inventory forecasting, ad experience, ad pacing, pricing, targeting, and efficient ad delivery.
- Invent and iterate on novel solutions to complex advertising challenges with rapid prototyping and deployment cycles.
- Design, build, and scale robust ML systems that power core ad platform capabilities
- Champion engineering excellence through best practices in code quality, system design, and operational reliability.
- Mentor and support junior engineers, fostering a culture of continuous learning and technical growth.
WHAT TO BRING
-
Bachelor's in computer science or equivalent experience
-
Minimum 5 years of hands-on experience developing and deploying large-scale machine learning systems.
-
Strong knowledge of AI/ML technologies, mathematics and statistics.
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Excellent communication, collaboration skills, and a strong teamwork ethic with both technical and non-technical audiences
-
Strong foundations in algorithms, data structures, and numerical optimization with experience in programming languages such as Python (primary), Java and SQL
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Familiarity with tools and frameworks such as Tensor Flow, Pytorch, Hugging libraries etc
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Proven proficiency in deep learning methodologies, including recurrent and sequence-based models.
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Hands-on experience with transformer architectures (e.g., BERT, GPT, ViT) for natural language and vision tasks.
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Strong understanding of multimodal embedding techniques for integrating text, image, audio, and structured data.
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Experience with LLM models such as GPT models, Claude, Gemini, Llama, etc.
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Strong grasp of LLM evaluation methodologies, experience with RAG architectures.
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A proven track record of thriving in a fast-paced, data-driven, and collaborative work environment is required.
NICE-TO-HAVES
- Experience in digital video advertising or digital marketing domain.
- Experience with forecasting models
- MS or PhD(preferred) in computer science or equivalent experience.
Location: Seattle / Santa Monica
#DISNEYTECH
The hiring range for this position in Los Angeles, CA area is $141,900 to $190,300 per year and in Seattle, WA is $148,700 - $199,400 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:
Ad Platforms
Job Posting Primary Business:
AP - Software Engineering:
Primary Job Posting Category:
Machine Learning
Employment Type:
Full time
Primary City, State, Region, Postal Code:
Seattle, WA, USA
Alternate City, State, Region, Postal Code:
USA - CA - 2450 Broadway
Date Posted:
2026-01-22
総閲覧数
0
応募クリック数
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模擬応募者数
0
スクラップ
0
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Hulu (Disney)について

Hulu (Disney)
AcquiredThe happiest place on earth.
1,001-5,000
従業員数
Santa Monica
本社所在地
レビュー
3.7
10件のレビュー
ワークライフバランス
2.8
報酬
3.5
企業文化
4.2
キャリア
2.9
経営陣
2.7
65%
友人に勧める
良い点
Great team culture and supportive colleagues
Flexible hours and work arrangements
Creative freedom and interesting work
改善点
Work-life balance challenges and long hours
High-pressure and stressful environment
Management issues and disorganization
給与レンジ
59件のデータ
Mid/L4
Senior/L5
Lead
Mid/L4 · Senior Data Engineer
2件のレポート
$227,444
年収総額
基本給
$174,957
ストック
-
ボーナス
-
$219,624
$235,263
面接体験
3件の面接
難易度
3.0
/ 5
期間
21-35週間
体験
ポジティブ 0%
普通 67%
ネガティブ 33%
面接プロセス
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Online Assessment
5
Onsite/Virtual Interviews
6
Offer
よくある質問
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
ニュース&話題
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