Senior ML Platform Engineer – Real-Time Personalization

Disney Entertainment and ESPN Product & Technology; New York (NY); On-site; USD 149,000 - 199,000; Full time

Benefits offered by this job

Bonus & equity

Medical benefits

Onsite location

Job summary

Disney Entertainment and ESPN Product & Technology’s News ML team is building real-time, personalized news experiences across web, mobile, and connected TV. The role leads end-to-end ML initiatives, develops data pipelines and feature libraries, and delivers ML solutions such as recommendation systems and autogenerated tagging.

You will work with product, editorial, and engineering stakeholders, mentoring engineers and advancing observability and CI/CD practices in a fast-paced media

Qualifications

• Bachelor’s degree or equivalent experience in a relevant field.
• 5+ years building and operating ML engineering systems in production.
• Expertise in data science, deep learning, or statistics for real-world problems.
• Ability to design across data collection, analysis, feature engineering, training, and low-latency serving.
• Experience with backend microservices using REST and cloud AWS.

Responsibilities

• Lead ML initiatives end-to-end from design to deployment and operations.
• Build ML infrastructure for data pipelines and workflow orchestration.
• Develop data discovery tooling and feature libraries for ML use cases.
• Deliver solutions across engineering needs like recommender systems, object detection, autogenerated tagging, and RAGs.
• Collaborate with product, editorial, and engineering teams to translate requirements into technical solutions.
• Mentor engineers to improve ownership, collaboration, and quality.

Skills

Data science

Deep learning

5+ years

REST

Team leadership

Education

Bachelor’s degree in CS/IS/Statistics/Math

Tools

AWS

Spark

Databricks

Kinesis

Kafka

Datadog

CI/CD

Job description

Disney Entertainment and ESPN Product & Technology’s News ML team is building real-time, personalized news experiences across web, mobile, and connected TV. The role leads end-to-end ML initiatives, develops data pipelines and feature libraries, and delivers ML solutions such as recommendation systems and autogenerated tagging.

You will work with product, editorial, and engineering stakeholders, mentoring engineers and advancing observability and CI/CD practices in a fast-paced media