Sr Manager, Machine Learning Engineering

USA - NY - 1211 Avenue of the Americas

The Walt Disney Company

The mission of The Walt Disney Company is to be one of the world's leading producers and providers of entertainment and information.

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Job Posting Title:

Sr Manager, Machine Learning Engineering

Req ID:

10055100

Job Description:

Overview:

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 interested in leading the Model Engineering team (part of ML Platform) that builds interfaces, tooling and services to develop and deploy ML models, host and manage them in a high-availability and low-latency production ecosystem. The leader will drive the technical strategy, partner with platform partners and stakeholders, seek feedback, and focus on continuous development and improvement of the ML runtime, and simplified user onboarding.

Responsibilities:

  • Lead and grow a team to build state of the art ML runtime environment

  • Provide technical direction for the Model Engineering team

  • Partner with Product and stakeholders to deliver innovative platform solutions 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:

  • 10+ years of software experience working in large scale, real-time distributed systems

  • 3+ years of leadership 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

Preferred Qualifications:

  • Familiarity with ML pipelines, data ecosystem and AWS technologies

  • Building ML infrastructure, streaming ML applications

  • Experience shipping entertainment and media applications for streaming purposes

Required Education:

  • Bachelor’s degree in Computer Science (or related field) and/or equivalent work experience

The hiring range for this position is $197,866 to $228,800 per year, which factors in various geographic regions. 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.

Job Posting Segment:

Product & Data Engineering

Job Posting Primary Business:

Product & Data Engineering

Primary Job Posting Category:

Machine Learning

Employment Type:

Full time

Primary City, State, Region, Postal Code:

New York, NY, USA

Alternate City, State, Region, Postal Code:

USA - CA - 2450 Broadway, USA - CA - Market St, USA - WA - 925 4th Ave

Date Posted:

2023-07-21
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Tags: Agile AWS Computer Science Distributed Systems Docker Engineering GCP Kubernetes Machine Learning ML infrastructure ML models Pipelines Streaming

Perks/benefits: Career development Equity / stock options Salary bonus Transparency

Regions: North America South America
Country: United States

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