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Discovery

Bellevue, WA 02-05-2021
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  • Paid
  • Full Time
  • Senior (5-10 years) Experience
Job Description

Overview

As television and media habits change, our mission remains true to the principles that founded Discovery – every day we seek to ignite people's curiosity to engage, entertain and enlighten the world around them through amazing viewing experiences.

The Direct to Consumer Group is a technology company within Discovery. We are building a global streaming video platform (OTT) which covers search, recommendation, personalization, catalogue, video transcoding, global subscriptions and really much more. We build user experiences ranging from classic lean-back viewing to interactive learning applications. We build for connected TVs, web, mobile phones, tablets and consoles for a large footprint of Discovery owned networks (Discovery, Food Network, Golf TV, MotorTrend, Eurosport, Discovery Play, and many more). This is a growing, global engineering group crucial to Discovery's future.

We are hiring Senior Software Engineers to join the Personalization, Recommendation and Search team. As part of a rapidly growing team, you will own complex systems that will provide a personalized and unique experience for millions of users across over 200 countries for all the Discovery brands. You will be responsible for designing and implementing state-of-the-art ML algorithms and systems to personalize the entire experience for our users. You will apply advanced ML techniques to build Recommender and Search systems.

You will lead by example and define the best practices, will set high standards for the entire team and for the rest of the organization. You have a successful track record for ambitious projects across cross-functional teams. You are passionate and results-oriented. You strive for technical excellence and are very hands-on. Your co-workers love working with you. You have built respect in your career through concrete accomplishments.

Requirements
• 7+ years of experience designing, building, deploying, testing, maintaining, monitoring and owning scalable, resilient and distributed machine learning algorithms and systems.
• Expertise with Machine Learning algorithms applied to Recommender Systems and Search.
• Proficiency in operating machine learning solutions at scale, covering the end-to-end ML workflow.
• Experience with offline experimentation and A/B testing.
• Deep knowledge of ML tools and frameworks (TensorFlow, Keras, pyTorch, scikit-learn, Spark, ...).
• Proficiency in programming languages such as Python or Scala.
• Strong understanding of modern approaches to Recommendation or Search (GBDT, CNN, LSTM, GRU, HRNN, transformers, siamese neural networks, variational auto-encoders, ...).
• Experience with at least one of Deep Learning, Contextual Multi-Armed Bandits, Reinforcement Learning, Causal Inference.
• Familiarity with real-world ML systems (configuration, data collection, data verification, feature extraction, resource and process management, analytics, training, serving, validation, experimentation, monitoring).
• Understanding of batch and streaming data processing techniques.
• Obsession for service observability, instrumentation, monitoring and alerting.
• Knowledge of AWS or similar cloud platforms.
• Familiarity with CI/CD tools (CircleCI, Jenkins or similar) to automate building, testing and deployment of the ML algorithms and to manage the infrastructure (Pulumi, Terraform or CloudFormation).
• Masters in Computer Science or related discipline.
• Must have the legal right to work in the United States

If you are motivated to succeed, self-driven and excited by the idea that your work will define Discovery's success and the daily viewing experience for millions of users, please connect with us, we would love to chat with you!

Nearest Major Market: Seattle

Nearest Secondary Market: Bellevue

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Company Profile
Discovery

Discovery, Inc. is the global leader in real life entertainment. We serve passionate fans with content that inspires, informs, and entertains, providing leadership across deeply loved and trusted brands, such as Discovery Channel, TLC, Animal Planet, HGTV, Food Network, and Travel Channel.