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Machine Learning Engineer

Company Description

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.

Job Description

As part of the global Operations & Technology organization, the Data & Analytics group (D&A) is focused on the data strategies for the future, covering the entire analytics life cycle – data engineering, data architecture, data platforms, data analysis, data viz, and data science. We support NBCU’s vast portfolio of brands – from broadcast, cable, news, and sports networks to film studios, world-renowned theme parks, and a diverse suite of digital properties. We take pride in providing NBCUniversal with data to advise and shape strategic business decisions. 

The Data & Analytics team is looking for a passionate Machine Learning Engineer adept at building the next generation of analytics solutions and ML pipelines. The candidate will be working closely with internal stakeholders, data engineers, visualization experts, and other technologists across one or more of our main subject areas. 

This role is right for you if you are a subject matter expert in designing end-to-end data science solutions and can maintain the fine balance of business acumen and deep technical knowledge. You are a passionate problem solver who is looking to build the next generation of products and applications for ML models. You are also a hands-on coder and architect who can create scalable (even self-healing) machine-learning pipelines in the cloud. 

Responsibilities: 

  • Drive end-to-end MLOps development to create scalable production ML pipelines (e.g., feature creation, training, and inference) for various lines-of-business, inclusive of Consumer, Film, Streaming, and Ad Sales. These automated products will aid in the timely decision-making process for marketing, strategy, and targeted advertising 
  • Establish best practices for engineering, monitoring, operationalizing, and improving automated ML models and APIs, with consideration for the levels of user expertise, cloud ecosystem capabilities, and transferrable standards 
  • Lead the prototype, architecture, and selection of ML and Data Science platforms, cognizant of the varied levels of user expertise, technical capabilities, and trends 
  • Partner closely with business, product owners, engineering, and data science teams to implement design patterns that optimize performance, cost, security, and scale, and that complement company-wide architectural standards 
  • Support advanced analytics efforts and deep-dive analysis to answer specific business questions, and develop augmented-analysis tools to enable efficient business decisions 
  • Mentor and guide engineering and data science peers in building a comprehensive set of tools, knowledge, and standards that can be democratized across the organization 

Qualifications

  • Strong understanding of applied statistics and machine learning algorithms, experience in methodologies for regression, classification, clustering, and causality 
  • 8+ years of data science experience, with demonstrated proficiency using SQL and Python in building analytical solutions 
  • 3+ years of experience building production-deployed, well-monitored MLOps solutions to solve business problems, with particular preference for the media industry 
  • Experience in AutoML, NLP, and Deep Learning frameworks that enrich MLOps efficacy 
  • Intimate familiarity with ML architectures (e.g., MLflow) and workflows on the cloud (i.e., AWS, GCP, Azure) 
  • Hands-on experience with Snowflake, Databricks, Spark, Airflow, or related cloud-based big-data storage and orchestration technologies 
  • Bachelor's/Master’s degree – or equivalence with experience – in Computer Science, Data/Decision Science, Data Engineering, Quantitative Economics, or Mathematics 

Desired Characteristics:

  • Direct experience working with media/entertainment and ad sales datasets and platforms is a plus – Nielsen, comScore, FreeWheel, mParticle, and Salesforce 
  • Ability to report and demonstrate model-development progress to stakeholders by visualizing results and communicating plans, benchmarks, and improvements 
  • Strong understanding of Agile principles and best practices, including CI/CD principles 
  • Comfortable with ambiguity and making decisions in a dynamic, fast-paced environment 
  • Excellent verbal and written skills with the ability to communicate data stories effectively across all levels of the organization, both technical and non-technical 

Additional Requirements:

  • Fully Remote: This position has been designated as fully remote, meaning that the position is expected to contribute from a non-NBCUniversal worksite, most commonly an employee’s residence.

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: $130,000 - $170,000 (bonus eligible)

We are accepting applications for this position on an ongoing basis.

Additional Information

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. 

If you are a qualified individual with a disability or a disabled veteran, you have the right to request a reasonable accommodation if you are unable or limited in your ability to use or access nbcunicareers.com as a result of your disability. You can request reasonable accommodations by emailing [email protected].

For LA County and City Residents Only:  NBCUniversal will consider for employment
qualified applicants with criminal histories, or arrest or conviction records, in a manner
consistent with relevant legal requirements, including the City of Los Angeles' Fair Chance
Initiative For Hiring Ordinance, the Los Angeles' County Fair Chance Ordinance for Employers, and the California Fair Chance Act, where applicable.

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Average salary estimate

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What You Should Know About Machine Learning Engineer, NBCUniversal

At NBCUniversal, we're looking for a passionate Machine Learning Engineer to join our vibrant Data & Analytics team located in Englewood Cliffs, New Jersey. In this role, you'll play a critical part in designing and implementing cutting-edge analytics solutions and machine learning (ML) pipelines that empower various lines of our diverse business—from film to streaming and advertising. Here, creativity meets technology, as you’ll have the opportunity to work closely with data engineers, visualization experts, and numerous stakeholders to craft scalable ML solutions. Your expertise will help shape strategic business decisions and improve our overall data-driven approach. You'll take the lead on end-to-end MLOps development, establishing best practices and working with modern cloud technologies like AWS and Azure. We value collaboration and mentorship, so if you have a knack for guiding teams and sharing knowledge, you’ll thrive in this dynamic environment. With a salary range of $130,000 - $170,000 and comprehensive benefits, we believe in supporting our engineers who are ready to innovate and make a difference. If you're excited about leveraging your deep technical knowledge and problem-solving skills to build the future of entertainment analytics, then this position is perfect for you.

Frequently Asked Questions (FAQs) for Machine Learning Engineer Role at NBCUniversal
What does a Machine Learning Engineer do at NBCUniversal?

At NBCUniversal, a Machine Learning Engineer is integral to our Data & Analytics team, focusing on building robust ML solutions and pipelines that enhance decision-making across various business lines. From creating automated products for marketing and strategy to establishing best practices for monitoring and improving ML models, this position encompasses a wide range of responsibilities aimed at driving innovation.

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What qualifications are needed for the Machine Learning Engineer role at NBCUniversal?

To qualify for the Machine Learning Engineer position at NBCUniversal, candidates should have over 8 years of data science experience with proficiency in SQL and Python. Additionally, experience in production-deployed MLOps solutions, familiarity with ML frameworks, and knowledge of cloud technologies are key. A Bachelor's or Master's degree in a related field is also required.

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Is the Machine Learning Engineer position at NBCUniversal remote?

Yes! The Machine Learning Engineer role at NBCUniversal is designated as fully remote. This means you can contribute to our team from your home, allowing for flexibility and work-life balance while still engaging in impactful projects.

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What is the salary range for a Machine Learning Engineer at NBCUniversal?

The salary range for a Machine Learning Engineer at NBCUniversal is between $130,000 and $170,000. The role is also bonus eligible, which reflects our commitment to hiring top talent in the industry.

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What technologies should a Machine Learning Engineer at NBCUniversal be familiar with?

Candidates for the Machine Learning Engineer role at NBCUniversal should have hands-on experience with cloud technologies, big-data storage solutions like Snowflake and Databricks, as well as orchestration platforms like Airflow. Proficiency with ML architectures and tools is essential for success in this position.

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How does NBCUniversal support diversity and inclusion in the workplace?

NBCUniversal is committed to fostering a diverse, equitable, and inclusive workplace. Our initiatives are driven by the voices of our employees and the communities we serve, ensuring an environment where every team member feels supported and valued.

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What opportunities for growth exist for a Machine Learning Engineer at NBCUniversal?

At NBCUniversal, a Machine Learning Engineer has ample opportunities for growth and mentorship. You’ll work alongside talented professionals from various fields, with chances to lead projects, guide peers, and continuously broaden your expertise in a cutting-edge, fast-paced environment.

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Common Interview Questions for Machine Learning Engineer
Can you describe your experience with MLOps and how it relates to the role at NBCUniversal?

When discussing your MLOps experience, highlight specific projects where you've implemented scalable ML pipelines. Explain your understanding of best practices in monitoring and operationalizing models, and consider mentioning any relevant challenges you faced and how you overcame them.

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How would you approach building a machine learning model for NBCUniversal's diverse business lines?

In your answer, reflect on how you would begin by understanding the specific data and business needs of each line, whether it's film, streaming, or advertising. Discuss your process for feature engineering, model selection, and validation, ensuring that the solutions are tailored and impactful.

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What tools do you prefer for data analysis and why?

Share your preferred tools, such as Python libraries, SQL databases, or cloud platforms. Discuss why these tools work best for you based on factors such as ease of use, scalability, and the specificity of tasks you regularly perform in data analysis.

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How do you keep up with the latest trends in machine learning and data science?

Discuss the resources you utilize, such as academic journals, online courses, or professional networks. Emphasize your commitment to continuous learning and how you apply new insights to your work, particularly in the fast-changing media landscape at NBCUniversal.

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Can you discuss a challenging problem you solved using machine learning?

Prepare a specific example where you identified a problem, assessed possible solutions, implemented a model, and evaluated its success. Highlight your analytical thinking, problem-solving skills, and the impact of your solution on the business.

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What is your experience with cloud-based technologies in ML deployments?

Be ready to discuss your experience with specific cloud platforms like AWS, GCP, or Azure. Share examples of projects you've worked on that involved cloud-based deployments, emphasizing your role in optimizing performance and scalability.

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How do you ensure your machine learning models are interpretable?

Address the importance of model interpretability and discuss techniques you've used to enhance this, like SHAP values or LIME. Emphasize how you communicate model outcomes to non-technical stakeholders at NBCUniversal.

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What metrics do you consider important for evaluating model performance?

Discuss the metrics relevant to the specific business context of NBCUniversal, such as precision, recall, F1 score, or AUC-ROC. Show your understanding of how these metrics guide decisions in production environments.

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How do you handle data privacy and security in your ML projects?

Explain your awareness of data privacy regulations and best practices. Share examples of how you've implemented security measures in your projects to protect sensitive information, particularly in the media context.

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What strategies do you have for collaborating with cross-functional teams?

Highlight your experience working with various teams, including data engineers, product owners, and business stakeholders. Discuss the importance of clear communication and setting shared goals for successful collaboration in a dynamic environment like NBCUniversal.

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We are in business to create and deliver content so compelling it entertains, informs and shapes our world. We believe that the talent, creativity and diversity of our people are our greatest resources. We take our business seriously, but do no...

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Full-time, remote
DATE POSTED
November 26, 2024

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