Senior Machine Learning Engineer - Personalization

Dormont Manufacturing Co; New York (NY); On-site; USD 148,700 - 199,400; Full time

Job summary

Disney Streaming is seeking a seasoned ML engineer to lead recommendation and personalization algorithm research, development, and productionization. You will coordinate requirements with Product, Engineering, and Editorial teams and help shape the roadmap for algorithmic work.

The role is on‑site in New York, with collaboration across Engineering, Product, and Data teams to apply ML methods to meet strategic goals, optimize personalization, and enhance user experiences across Disney’s streaming

Qualifications

• 5+ 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.
• 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.
• Bachelor’s Degree in Computer Science, Math, Statistics, or related quantitative field.

Responsibilities

• 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 explain 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.

Skills

ML model development

Large-scale data analysis

Python

SQL

Production deployment

Big data analytics

Education

Bachelor's Degree in Computer Science, Math, Statistics, or related quantitative field

MS or PhD in statistics, math, computer science, or related quantitative field

Tools

Databricks

S3

Spark

Job description

Role Location

On‑site role requiring 4 days in‑person at designated office location.

Job Summary

Our team designs and builds models that directly shape the user experience – powering personalization and engagement across 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 lead recommendation and personalization algorithm research, development, and productionization for product areas, coordinate requirements and manage stakeholder expectations with Product, Engineering, and Editorial teams, and help set the roadmap for algorithmic work.

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 explain 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 Qualifications

• 5+ 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.
• 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.
• Bachelor’s Degree in Computer Science, Math, Statistics, or related quantitative field.

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.
• AWS, Databricks expertise.

Compensation & Benefits

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 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 other benefits.