Senior Machine Learning Engineer

New Today

Job Summary:
Our team develops and maintains state-of-the-art recommendation and personalization algorithms that serve hundreds of millions of users across Disney+, Hulu, ABC, and ESPN. As a key member of this team, you will collaborate closely with Engineering, Product, and Data teams to apply advanced machine learning techniques in support of strategic personalization initiatives. This is an Individual Contributor role focused on content recommendations. You will lead the research, development, deployment, and optimization of recommendation and personalization algorithms across product surfaces. You will also play a critical role in aligning technical solutions with stakeholder requirements and expectations, partnering with Product, Engineering, and Editorial teams. Beyond execution, you will help define the roadmap for algorithmic innovation—shaping approaches to feature development and contributing to broader company goals in the personalization and recommendation space. We are seeking a Senior Machine Learning Engineer to contribute to the development and deployment of cutting-edge recommendation and personalization algorithms that power user experiences across Disney+, Hulu, ABC, and ESPN. As a member of our team, you will work closely with Product, Engineering, and Data teams to build intelligent systems that serve hundreds of millions of users worldwide. In this role, you will be responsible for designing, implementing, and optimizing machine learning models for content recommendation and user personalization. You’ll take ownership of key projects, contribute to technical design and experimentation, and help translate product needs into scalable ML solutions. This is a strong individual contributor role for engineers with a solid foundation in machine learning and a passion for applied work in large-scale, real-world environments. You will have opportunities to grow your technical influence, deepen your domain expertise, and help drive innovation across personalization surfaces. Responsibilities: Developing and prototyping state-of-the-art Deep Neural Net algorithms for recommendation systems
Deliver a conceptual solution into production-level implementation & operation at scale, for global user services
Quickly learn our complex streaming recommendation systems and deep dive into individual components & systems as well as understand overall framework/architecture
Identify impactful opportunities to improve our business operations and develop practical solutions and plans to lift our business KPI’s.
Drive business decisions by data driven and pragmatic approach
Excellent written and oral communication skills
Basic Qualifications: Strong proficiency in at least one of the following deep learning frameworks, tensorflow, pytorch
Experiences building and deploying full stack ML pipelines: data extraction, data mining, model training, feature development, testing, and deployment
Track record from design to full production of effective recommendation systems
Experience with cloud services in a production environment (particularly AWS)
Understanding of statistical concepts (., hypothesis testing, regression analysis)
Ability to articulate the usage and behavior of models and algorithms to both technical and non-technical audiences
Preferred qualifications: MS or PhD in statistics, math, computer science, or related quantitative field
Production experience with developing content recommendation algorithms at scale and familiar with metadata management, data lineage, and principles of data governance
Deep understanding in personalization challenges in homepage experience and proven records of developing effective solutions
Experience with: 5+ years of experience in developing highly scalable machine learning products
5+ years writing production-level, scalable Python codes
Required Education: Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience
The hiring range for this position in New York, NY & Seattle, WA is $145,400 to $195,000 per year, in Los Angeles/Santa Monica, CA is $138,900 to $186,200 per year and in San Francisco, CA is $152,100 to $203,900 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.
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Location:
Seattle

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