Sr Machine Learning Engineer

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

Join the News ML team to build and operate machine learning platforms for real-time, personalized news experiences across web, mobile, and connected TV.

Responsibilities

• Lead complex ML initiatives end-to-end, covering technical design, production deployment, and operational excellence
• Build ML infrastructure that supports the full lifecycle, including data pipelines and workflow orchestration
• Develop data discovery and quality tooling, plus feature libraries for downstream ML use cases
• Deliver data and ML solutions across engineering needs such as recommendation systems, object detection, autogenerated tagging solutions, and RAGs
• Collaborate with product, editorial, and engineering stakeholders to convert business requirements into technical solutions
• Prioritize technical workstreams to maximize highest-impact, time-sensitive outcomes
• Identify, communicate, and mitigate risks to support successful execution
• Advance engineering best practices across code quality, testing, CI/CD, observability, and incident response
• Mentor and coach engineers to strengthen ownership, collaboration, and continuous improvement
• Contribute to technical documentation and support knowledge sharing across teams

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Statistics, Math, or comparable field of study, and/or equivalent work experience
• 5+ years building and operating ML engineering systems in production environments
• Expertise in data science, deep learning algorithms, or statistical methods for real-world engineering problems
• Ability to work across the predictive stack, including data collection, data analysis, feature engineering, batch training, and low-latency online serving
• Experience designing and developing backend microservices for large-scale distributed systems using REST
• Cloud infrastructure experience, preferably AWS (Step Functions, Lambda, Glue, SQS, SNS, Personalize)
• Familiarity with developing and deploying Spark and ML pipelines
• Hands‑on experience with big data technologies such as Databricks, Kinesis, and Kafka
• Proven leadership, coaching, and mentoring skills, including inspiring and empowering a team toward business goals
• Experience with observability tools for metrics, logging, and monitoring such as Datadog
• Experience working in Agile/Scrum development environments
• Excellent communication skills and commitment to collaboration in a fast-paced, guest-focused environment

Technology

• REST
• AWS: Step Functions, Lambda, Glue, SQS, SNS, Personalize
• Spark
• Databricks
• Kinesis
• Kafka
• Datadog
• CI/CD
• RAGs
• Object detection
• Recommendation systems

Benefits

• Bonus and/or long-term incentive units may be provided as part of the compensation package
• Full range of medical, financial, and/or other benefits

Location: New York, NY (onsite)

Compensation: USD 148,700 - 199,400 per year