Sr Machine Learning Engineer - Personalization

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

Job summary

Dormont Manufacturing Co in New York is seeking a Machine Learning Engineer focused on algorithm development and personalization. The role involves utilizing advanced ML methods to optimize user experiences across products.

Key responsibilities include developing ETL pipelines, maintaining algorithms, and collaborating with multiple teams. Candidates should have at least 5 years of experience in machine learning and be proficient in Python and SQL. Competitive compensation and comprehensive benefits are offered.

Qualifications

• 5+ years of experience developing machine learning models and performing large-scale data analysis.
• 5+ years writing production-level, scalable code (Python, SQL).
• Strong understanding of modern machine learning methods and models.

Responsibilities

• Utilize cutting-edge machine learning methods to develop algorithms for personalization and recommendations.
• Develop and maintain ETL pipelines using orchestration tools such as Airflow and Jenkins.
• Collaborate with Product and Business Stakeholders to define new personalization opportunities.

Skills

Machine learning model development

Python programming

SQL proficiency

Data engineering

Algorithm development

ETL pipeline development

Communication skills

Education

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

Tools

AWS

Databricks

Apache Spark

Job description

Job Summary

Our team designs and builds models that directly shape the user experience – powering personalization and engagement across our Disney Streaming 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 be expected to lead recommendation and personalization algorithm research, development, and productionization, 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 serve as the point person in explaining 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.
• Collaboration with Product and Business Stakeholders: Identify and define new personalization opportunities and work with other data teams to improve data collection, experimentation, and analysis.

Required Qualifications

• 5+ years of experience developing machine learning models, performing large‑scale data analysis, and/or data engineering.
• 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 building big‑data solutions using technologies like Databricks, S3, and Spark.
• Ability to gauge the complexity of machine learning problems and 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 a related quantitative field.

Preferred Qualifications

• MS or PhD in statistics, math, computer science, or a 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.
• Familiarity with metadata management, data lineage, and principles of data governance.
• Experience loading and querying cloud‑hosted databases.

Experience With

• AWS, Databricks

Compensation

Hiring range for this position in New York, NY: $148,700 - $199,400 per year. In Santa Monica, CA: $141,900 - $190,300. Base pay may vary based on experience and geographic location. Bonus and/or long‑term incentive units may be provided, plus a full range of medical, financial, and other benefits.