採用
福利厚生
•Healthcare
•401(k)
•Equity
必須スキル
Python
Java
SQL
Machine Learning
Deep Learning
Transformer Architectures
Multimodal Embeddings
Large Language Models
RAG
TensorFlow
PyTorch
Hugging Face
Job Posting Title:
Lead Machine Learning Engineer, Ad Platforms
Req ID:
10137358
Job Description:
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.
Ad Platforms is responsible for Disney’s industry-leading ad technology and products – driving advertising performance, innovation, and value in Disney’s sports, news, and entertainment content, across all media platforms.
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
- Minimum 7 years of hands-on experience developing and deploying large-scale machine learning systems.
- Strong knowledge of AI/ML technologies, mathematics and statistics.
- 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
- Familiarity with tools and frameworks such as Databricks, Tensor Flow, Pytorch, Hugging libraries etc
- Proven proficiency in deep learning methodologies, including recurrent and sequence-based models.
- Hands-on experience with transformer architectures (e.g., BERT, GPT, ViT) for natural language and vision tasks.
- Strong understanding of multimodal embedding techniques for integrating text, image, audio, and structured data.
- Experience with LLM models such as GPT models, Claude, Gemini, Llama, etc.
- Strong grasp of LLM evaluation methodologies, experience with RAG architectures.
- 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.
Required Education:
Bachelor's (MS or PhD preferred) in Computer Science, Software Engineering, or a related field
Location: Seattle / Santa Monica
#DISNEYTECH
The hiring range for this position in Santa Monica, CA is $171,600 to $230,100 per year and in Seattle is $179,700 to $241,000. 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:
Santa Monica, CA, USA
Alternate City, State, Region, Postal Code:
USA - WA - 925 4th Ave
Date Posted:
2026-01-21
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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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