We create world-class content, which we distribute across our portfolio of film, television, and streaming, and bring to life through our theme parks and consumer experiences. We own and operate leading entertainment and news brands, including NBC, NBC News, MSNBC, CNBC, NBC Sports, Telemundo, NBC Local Stations, Bravo, USA Network, and Peacock, our premium ad-supported streaming service. We produce and distribute premier filmed entertainment and programming through Universal Filmed Entertainment Group and Universal Studio Group, and have world-renowned theme parks and attractions through Universal Destinations & Experiences. NBCUniversal is a subsidiary of Comcast Corporation.

Here you can be your authentic self. As a company uniquely positioned to educate, entertain and empower through our platforms, Comcast NBCUniversal stands for including everyone. Our Diversity, Equity and Inclusion initiatives, coupled with our Corporate Social Responsibility work, is informed by our employees, audiences, park guests and the communities in which we live. We strive to foster a diverse, equitable and inclusive culture where our employees feel supported, embraced and heard. Together, we’ll continue to create and deliver content that reflects the current and ever-changing face of the world.

As part of the Direct-to-Consumer Decision Sciences team, the Principal Machine Learning Engineer will lead a team of talented Machine Learning Engineers, mentoring and guiding them to deliver Machine Learning solutions that unleashes the power of our streaming data.  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.

The ideal candidate will have a proven track record of leading successful Machine Learning projects, a strong technical background, and excellent communication skills.
 
Responsibilities include, but are not limited to:
 

• Lead team in design, build, testing, scaling and maintaining Machine Learning pipelines, according to business and technical requirements
• Identify and engineer relevant features to improve model performance and interpretability
• Deliver observable, reliable and secure software, embracing “you build it you run it” mentality, and focus on automation
• Continually work on improving the codebase and have active participation and oversight in all aspects of the team, including agile ceremonies
• Take an active role in story definition, assisting business stakeholders with acceptance criteria
• Work closely with cross-functional teams, including product managers, data scientists, and software engineers, to translate business requirements into technical solutions
• Work with other Principal Engineers and Architects to share and contribute to the broader technical vision
• Stay current with emerging trends in machine learning, deep learning, and artificial intelligence, and drive innovation by evaluating and integrating new techniques
• Develop and champion best practices, striving towards excellence and raising the bar within the department
• Operationalize data processing systems (dev ops)

Basic Requirements

• Advanced Degree in Computer Science, Machine Learning, Statistics, or Related Field: Master’s or Ph.D. preferred, or equivalent experience in a relevant field
• 8+ years relevant experience in Data and/or Software Engineering
• 4+ years experience in Machine Learning Engineering
• Proven track record of leading and mentoring teams of Machine Learning Engineers
• Experience of near Real Time & Batch Data Pipeline development and deployment
• Programming skills in one or more of the following: Python, Java, Scala, R, SQL and experience in writing reusable/efficient code to automate analysis and data processes
• Experience with Google Cloud Platform or other Cloud Platforms
• A good understanding of CI/CD pipelines and automated testing
• Familiarity with MLOps practices and tools for model deployment, monitoring, and maintenance.
• Experience with containerisation tools such as Docker, Kubernetes
• Hands on programming experience of the following (or similar) technologies: Apache Beam, Scio, Apache Spark, Apache Kafka, Flink or Snowflake
• Passion for quality and observability
• Understanding of application security standards

Desired Characteristics

• Experience with graph-based data workflows using Apache Airflow
• Strong Test-Driven Development background, with understanding of levels of testing required to continuously deliver value to production
• Experience with large-scale video assets
• Ability to work effectively across functions, disciplines, and levels
• Team-oriented and collaborative approach with a demonstrated aptitude, enthusiasm and willingness to learn new methods, tools, practices and skills
• 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

Additional Requirements:

Hybrid: This position has been designated as hybrid, generally contributing from the office a minimum of three days per week.

This position is eligible for company sponsored benefits, including medical, dental and vision insurance, 401(k), paid leave, tuition reimbursement, and a variety of other discounts and perks. Learn more about the benefits offered by NBCUniversal by visiting the Benefits page of the Careers website. Salary range: $165,000 - $210,000 (bonus and long-term incentive eligible). 

As part of our selection process, external candidates may be required to attend an in-person interview with an NBCUniversal employee at one of our locations prior to a hiring decision.

NBCUniversal's policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law. 

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