Disney Entertainment & ESPN Product Technology is looking to research, develop, deploy, and optimize ML applications to shape the roadmap for algorithmic innovation, ensuring scalable and impactful solutions aligned with stakeholder needs. They aim to enable the use of machine learning across heterogeneous environments and at every stage of a project's lifecycle.
Requirements
- Expertise in data science, (deep) learning algorithms, or statistical methods to solve real-world engineering problems
- Comfortable operating at all levels of the predictive stack, including data collection, feature engineering, batch training and low-latency online serving
- Experience with large-scale distributed data processing systems, cloud infrastructure such as AWS or GCP, and container systems such as Docker or Kubernetes
- Track record of building scalable ML applications, from design to full production
- Understanding of statistical concepts (e.g., hypothesis testing, regression analysis)
- Hands-on experience building models for video processing (such as clipping, cropping, understanding, search, …)
- Familiarity with developing and deploying Spark and ML pipelines
Responsibilities
- Drive data and ML driven solutions for diverse engineering use cases such as recommendation systems, object detection, anomaly detection, RAGs and translations
- Architect and build end to end ML models to drive data driven decisions
- Identify impactful opportunities to improve our business operations and develop practical solutions and plans to lift our business KPI’s
- Provide technical leadership to a team of engineers and work collaboratively with peers to achieve goals within deadlines
- Drive infrastructure innovation for scalable learning, inference, and monitoring
- Provide ML consultancy and mentorship
- Conduct in-depth data exploration and analysis
Other
- BS in computer science, statistics, math or a related quantitative field + 7 years of relevant SWE and MLEng experience
- Excellent written and oral communication skills
- Drive and maintain a culture of quality, innovation and experimentation
- Mentor colleagues on best practices and technical concepts of building large scale solutions
- The hiring range for this position in New York or Seattle is $175,800 to $235,700 per year, in San Francisco is $183,700 to $246,400 per year, and in Los Angeles is $167,700 to $224,900 per year.
