AddressJob Summary:
Engineering Manager, Production ML
The vision of the Machine Learning (ML) Engineering team at Disney 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 maximize the positive business impact of all ML at Disney streaming by supporting key product functions like personalization and recommendation, fraud and abuse prevention, capacity planning, subscriber growth and lifecycle intelligence, and so on.
We’re looking for an engineering leader who interfaces with various domains to productionize AI/ML applications, build tooling and services to federate and process context for the ML models, enable and support event-triggered models in a high-availability and low-latency production ecosystem. The leader will drive the technical strategy, partner with the platform team and various domains, seek feedback, and focus on continuous development and improvement of the ML runtime, and simplified user onboarding.
Responsibilities:
- Lead and grow a team that onboards and scales ML solutions in production
- Provide technical direction for the production datasets and ML teams
- Partner with Product and stakeholders to deliver innovative tooling and services for scalable ML development and deployment
- Mentor and facilitate individual careers by optimizing for their success and growth
- Maintain a culture of innovation, quality, transparency, inclusion, and empathy
- Work in an Agile environment that focuses on collaboration and teamwork
Basic Qualifications:
- 8+ years of experience working in large scale, event-driven and real-time distributed systems
- Leadership and mentoring experience
- Experience building and deploying ML models in production
- Experience with cloud technologies in AWS or GCP as well as container systems such as Docker or Kubernetes
- Passion for building platforms and infrastructure excellence
- Excellent communication and people engagement skills
Nice to have:
- Familiarity with ML pipelines, data ecosystem and AWS technologies
- Building ML infrastructure, streaming ML applications
- Experience shipping entertainment and media applications for streaming purposes
Education:
- Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience
The hiring range for this position in San Francisco is $180,200 to $241,600 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.
