Machine Learning Engineer

Job Description

Responsibilities
Welcome to Peacock, the dynamic new streaming service from NBCUniversal. Here you'll find more than a job. You'll find a fast-paced, high-flying team for unique birds that want to be at the epicenter of technology, sports, news, tv, movies and more. Our flock works hard to connect people to what they love, each other and the world around them by creating shared experiences through culture-defining entertainment.

As a company, we embrace the power of difference. Our team is committed to creating an organization that champions diversity and inclusivity for all by curating content and a workforce that represents the world around us. We continue to challenge ourselves and the industry by being customer-centric, data-driven creatures of innovation. At Peacock, we are determined to forge the next frontier of streaming through creativity, teamwork, and talent.

Here you can fly to new heights!

Position Overview:

NBCUniversal, the global media company that brought you some of the world's most iconic television and film franchises, including: The Tonight Show, Saturday Night Live, Keeping Up With The Kardashians, The Real Housewives, Mr. Robot, The Voice, This Is Us, The Fast & The Furious, Jurassic Park, Minions, and more - is launching an all-new direct-to-consumer streaming service. It will seamlessly bring together the breadth and depth of NBCU's broadcast and cable television series, movie titles, premier sporting events, and renowned news reporting... all in one destination… all in one app.

Introducing Peacock, NBCUniversal's new streaming service that combines timeless shows and movies, exclusive originals, kids programming and current hits, with timely news, sports and pop culture. All together. All in one app.

We are building a world-class team of smart, hungry and fearless professionals who are energized by the possibility of working at the epicenter of content, technology and culture. Join us if you would like to be a part of this exciting initiative.

As part of the Direct-to-Consumer Decision Sciences team, the ML Engineer will be responsible for creating a connected data ecosystem that unleashes the power of our streaming data, as well as operations for machine learning models created by data scientists. We gather data from across all customer/prospect journeys in near real-time, to allow fast feedback loops across territories; combined with our strategic data platform, this data ecosystem is at the core of being able to make intelligent customer and business decisions.

In this role, the ML Engineer will share responsibilities in the development and maintenance of an optimized and highly available data pipelines that facilitate deeper analysis and reporting by the business, as well as provide support to the data science team to enable them to run machine learning models in a robust & resilient manner.

Responsibilities include, but are not limited to:
• Design, build, test, scale and maintain data pipelines from a variety of source systems and streams (Internal, third party, cloud based, etc.), according to business and technical requirements.
• Deliver observable, reliable and secure software, embracing ''you build it you run it'' mentality, and focus on automation and GitOps.
• Continually work on improving the codebase and have active participation in all aspects of the team, including agile ceremonies.
• Take an active role in story definition, assisting business stakeholders with acceptance criteria.
• Develop and champion best practices, striving towards excellence and raising the bar within the department.
• Develop solutions combining data blending, profiling, mining, statistical analysis, and machine learning, to better define and curate models, test hypothesis, and deliver key insights
• Operationalize data processing systems (dev ops)
• In cooperation w/ the data science team, productize machine learning models using workflow orchestrators such as Kubeflow or Apache Airflow

Qualifications/Requirements
• An Interest in data engineering, particularly as it relates to machine learning and data science
• Team-oriented and collaborative approach with a demonstrated aptitude, enthusiasm and willingness to learn new methods, tools, practices and skills
• Programming skills in one or more of the following: Java, Scala, R, Python, SQL and experience in writing reusable/efficient code to automate analysis and data processes
• Experience collaborating with other engineers using version control software such as Git or SVN
• Experience in processing structured and unstructured data into a form suitable for analysis and reporting with integration with a variety of data metric providers ranging from advertising, web analytics, and consumer devices
• Bachelors' degree with a specialization in Computer Science, Engineering, Physics, other quantitative field or equivalent industry experience.

Desired Characteristics
• Experience implementing scalable, distributed, and highly available systems using Google Cloud
• Hands on programming experience of the following (or similar) technologies: Apache Beam, Scio, Apache Spark, and Snowflake.
• Experience in progressive data application development, working in large scale/distributed SQL, NoSQL, and/or Hadoop environment.
• Experience building streaming data pipelines using Kafka, Spark or Flink
• Data modelling experience (operationalizing data science models/products) a plus
• Experience of near Real Time & Batch Data Pipeline development in a similar Big Data Engineering role.
• Experience with graph-based data workflows using Apache Airflow
• Experience building and deploying ML pipelines: training models, feature development, regression testing
• Experience with Test-Driven Development and understanding of levels of testing required to continuously deliver value to production.
• Ability to work effectively across functions, disciplines, and levels
• Ability to recognize discordant views and take part in constructive dialogue to resolve them
• Pride and ownership in your work and confident representation of your team to other parts of NBCUniversal.

Jobcode: Reference SBJ-rnp5no-18-218-254-122-42 in your application.