Lead ML Engineer

Key Skills

SQL, Python Programming, R Programming, AWS, Tableau, Scala Programming

Job Description

The vision of the Machine Learning (ML) Engineering team at Disney Streaming is to drive and enable ML usage across several domains in heterogeneous language environments and at all stages of a project’s life cycle, including ad-hoc exploration, preparing training data, model development, and robust production deployment. The team is invested in continual innovation on the ML infrastructure itself to carefully orchestrate a continuous cycle of learning, inference, and observation while also maintaining high system availability and reliability. We seek to find new ways to scale with our guest and partner base as well as the ever-growing need for ML and experiments.
In this role you will focus on partnering with software services and engineering groups to lead and drive ML applications in those domains. You will conduct data exploration, analysis to motivate and drive ML usage across the engineering and services teams, and provide ML consultancy. You will work on cross-functional products and push the envelope on data and ML focused solutions.

Responsibilities:

• Drive data and ML driven solutions for diverse engineering use cases
• Architect and build end to end ML workflows to drive data driven decisions
• Be a ML thought partner to our stakeholders
• Conduct data exploration, analysis and provide ML consultancy
• Drive and maintain a culture of quality, innovation and experimentation
• Work in an Agile environment that focuses on collaboration and teamwork

Basic Qualifications:

• 8+ years of software experience, with 5+ years of relevant ML experience
• Expertise with ML pipelines, algorithms, statistical methods, and analytics to solve real-world engineering problems
• Comfortable operating at all levels of the predictive stack and user behavior modeling including data collection, feature engineering, batch training and low-latency online serving
• Strong mathematical skills with knowledge of statistical methods

Preferred Qualifications:

• Familiarity with Python development ecosystem and technologies like Databricks, S3, Spark
• Experience with graph-based data workflows such as Apache Airflow, Meson
• Excellent communication and people engagement skills
• Drive and maintain a culture of quality, innovation and experimentation
• Mentor colleagues on best practices and technical concepts of building large scale solutions

Required Education