Comcast Machine Learning Co-op

Make your mark at Comcast -- a Fortune 30 global media and technology company. From the connectivity and platforms we provide, to the content and experiences we create, we reach hundreds of millions of customers, viewers, and guests worldwide. Become part of our award-winning technology team that turns big ideas into cutting-edge products, platforms, and solutions that our customers love. We create space to innovate, and we recognize, reward, and invest in your ideas, while ensuring you can proudly bring your authentic self to the workplace. Join us. You’ll do the best work of your career right here at Comcast. (In most cases, Comcast prefers to have employees on-site collaborating unless the team has been designated as virtual due to the nature of their work. If a position is listed with both office locations and virtual offerings, Comcast may be willing to consider candidates who live greater than 100 miles from the office for the remote option.)

Job Summary

Job Description

Program Overview

Discover opportunities designed to set your career in motion! The Comcast internship/co-op program will help you cultivate meaningful relationships, develop strong interpersonal and business skills, gain exposure to the day-to-day operations of a Fortune 40 media and technology company, and receive mentorship opportunities to expand your professional network.

This program immerses students into the daily operation of a contemporary media and technology company while working side-by-side with Comcast’s top innovators. The student becomes an integral part of the Comcast team working on creative, innovative, and thought-provoking projects within various business units.

Organization & Team Overview

Technology & Product team (TPX) designs, develops, delivers and supports innovative products and services that bring broadband, wireless, video and voice experiences to residential and business customers throughout the world, with more than 57 million customer relationships across the U.S. and Europe. The team also works to ensure the performance of our network in the U.S., including speeds and capacity that customers rely on to stay connected to what matters most, and builds and operates mission-critical systems, including those that monitor our network and its associated cloud infrastructure.

Technology & Product is focused on providing an excellent customer experience, which goes beyond updating existing products and services and developing others that customers soon realize they can’t live without; it’s also about making those products simple, personal and awesome – and building in the proactive support and best-in-class service that optimize the experience and differentiate our offerings from those of our competitors.

Our team, Global Product organization, as part of TPX, builds services to enable personalization of content and monetization of content that is served to millions of customers. Our team, called Arbitration Engine, is a team who builds multiple services to enable display advertisements on all TV platforms supported globally, including Sky, Xumo, Comcast, and builds the Machine Learning algorithms that drive the choice of best and most relevant advertisement served to customers, while aiming increasing the revenue with the choice. The impact of our team is directly related to revenue generated from targeted and personalized endemic advertisements and targeted and personalized monetizable assets on the TV platforms. The team is comprised of engineers and machine learning researchers working together to build the best machine learning models and build the best engineering infrastructure to bring the content served using models to customers in a scalable, reliable and performant way. Our team also works on personalization of content, bring the most relevant content to customers, so users can easily find the content they would like to watch. This involves a mix of ranking models, and output and loss aggregated revenue-objectives added to ranking models. Our engineering infrastructure serves global customer traffic, with double digit P99 latency, highly reliable and scalable.

Role Description

Are you passionate about building cutting-edge machine learning models and engineering systems that impact millions of customers globally? Do you thrive on solving complex challenges in content personalization, content monetization, display advertisement, ad-relevancy and scalable infrastructure? Join our highly motivated team at the Arbitration Engine, where we combine advanced machine learning research with world-class engineering to deliver personalized and targeted content on TV platforms like Sky, Xumo, and Comcast. Be part of a team that directly drives revenue through innovative solutions, all while creating exceptional experiences for customers worldwide!

As a Machine Learning Co-op on the Arbitration Engine team, you will work alongside experienced engineers and researchers to develop and optimize machine learning models that power personalized content and targeted advertisements for millions of global customers. You will contribute to building ranking models, designing algorithms to maximize revenue objectives, and improving the relevance of content served to users. Additionally, you will help enhance our scalable and reliable engineering infrastructure, ensuring low-latency delivery of personalized experiences. This role offers the opportunity to gain hands-on experience in applying machine learning to real-world problems, collaborate in a fast-paced environment, and make a tangible impact on the future of content personalization and monetization.

Every day, you will have the opportunity to collaborate closely with Machine Learning researchers to design and implement innovative solutions for personalized content and targeted advertisements. You will work on building robust data pipelines to collect, process, and prepare large-scale datasets for training machine learning models, ensuring data quality and scalability. Additionally, you will contribute to developing pipelines for training machine learning models, optimizing them for performance and efficiency. You will also play a key role in creating frameworks for offline evaluation and validation of new models, enabling the team to assess their effectiveness and refine them before deployment. Furthermore, you will work on setting up and running online controlled experiments (A/B tests) to test the performance of new models in real-world scenarios, measuring their impact on personalization, relevance, and revenue objectives. This role provides a hands-on opportunity to work across the entire machine learning lifecycle, from data preparation to model deployment and evaluation, in a highly collaborative and impactful environment.

What are some interesting problems the student will work on?

In your role, you will collaborate with Machine Learning researchers to explore and experiment with innovative ideas aimed at improving personalization, increasing conversions from targeted advertisements, and enhancing ad relevancy. You will dive deep into understanding the vast datasets available, identifying opportunities to create new metrics and signals that measure the impact of our models and improve their performance. This includes designing and building pipelines to process large-scale datasets, enabling advanced research and experimentation. You will also develop frameworks to evaluate the performance of new models, both offline and in real-world scenarios, ensuring they meet our objectives of scalability, reliability, and user satisfaction.

Some of the exciting problems our team is tackling include optimizing the balance between improving conversions of targeted advertisements and maintaining user engagement, ensuring that revenue growth from monetizable assets does not come at the cost of user happiness. You will work on discovering and incorporating new signals into our data to enhance revenue generation while preserving a seamless and enjoyable user experience. Additionally, you will have the opportunity to contribute to the development of ranking models and algorithms that align with aggregated revenue objectives, helping to shape the future of personalized content and monetization strategies on a global scale.

Where can this student make an impact?

As a Machine Learning Co-op on the Arbitration Engine team, you will have the opportunity to make a significant impact on how personalized content and targeted advertisements are delivered to millions of customers worldwide. Your contributions to building and optimizing machine learning models, designing data pipelines, and developing evaluation frameworks will directly influence the relevance and effectiveness of the content served on platforms like Sky, Xumo, and Comcast. By improving ad conversions, enhancing personalization, and discovering new signals to train advanced models, you will play a key role in driving revenue growth while maintaining user engagement and satisfaction. Your work will not only shape the future of content monetization but also ensure that customers have a seamless and enjoyable experience with the content they consume. Your impact will also include publishing research papers about the ideas implemented to serve customers driving revenue growth while maintaining user engagement.

Job Responsibilities

Responsibilities include but are not limited to:

• Collaborate with Machine Learning researchers to experiment with and implement innovative ideas for improving personalization, ad relevancy, and targeted advertisement conversions.
• Build and maintain data pipelines to process large-scale datasets for training and evaluating machine learning models.
• Develop frameworks for offline evaluation and validation of machine learning models to measure their performance and effectiveness.
• Assist in setting up and running online controlled experiments (A/B tests) to test new models in real-world scenarios and measure their impact.
• Research and identify new metrics and signals to enhance model training and improve revenue generation while maintaining user engagement and satisfaction.
• Contribute to the design and optimization of scalable, reliable, and high-performance engineering infrastructure to support machine learning workflows.
• Other duties and responsibilities as assigned.

Preferred Skills

• Proficiency in Python and experience with data processing libraries such as Pandas. 
• Hands-on experience with PySpark and Databricks for large-scale data processing. 
• Strong understanding of data engineering concepts, including building and maintaining data pipelines. 
• Knowledge of Machine Learning techniques, including experience with frameworks like PyTorch or TensorFlow. 
• Familiarity with recommendation systems and large language models (LLMs). 
• Experience designing and analyzing A/B tests and working with metrics to evaluate model performance. 
• Solid foundation in statistics and its application to machine learning and experimentation. 
• Understanding of scalable distributed systems and their role in processing and serving large-scale data. 
• Preferred Majors: Computer Science, Data Science, Artificial Intelligence, Machine Learning, Software Engineering, Electrical Engineering, Mathematics, Statistics

Minimum Qualifications and Eligibility Requirements

• Currently pursuing a bachelor’s degree from Drexel University, with a cooperative learning track.
• Available to work 40 hours per week for 6 months starting September 22, 2025, through March 27, 2026.
• Authorized to work in the United States with no current or future sponsorship needs
• Available to report in-person to the work location on the job posting
• Comcast is an Affirmative Action/EEO employer M/F/D/V

Skills

Accountability, Communication, Professional Etiquette, Relationship Building, Resilience, Teamwork

Compensation

Base Pay: $32.00

Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work.    Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus.  Additionally, Comcast provides best-in-class Benefits to eligible employees.  We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most.  That’s why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality – to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the compensation and benefits summary on our careers site for more details. 

The application window is 30 days from the date job is posted, unless the number of applicants requires it to close sooner or later.

Education

Certifications (if applicable)

Relevant Work Experience

0-2 Years

Comcast is proud to be an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law.