Comcast Corporation
Comcast Machine Learning- Content Discovery Graduate Research Intern
Comcast Corporation, Washington, District of Columbia, us, 20022
Make your mark at Comcasta 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 SummaryThis job code is to be used for internships and co-ops. It is not to be used for temporary or contract workers.
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
The Content Discovery team is responsible for powering the search, browse, recommendations, personalization, and voice capabilities for our entertainment products.
Role Description
We are looking for a passionate and skilled PhD student to join our research team as a Machine Learning Research Intern. In this role, you will work on cutting-edge problems in the domains of personalization, recommendation systems, and natural language processing (NLP). This is an excellent opportunity for a PhD student to apply advanced machine learning (ML) techniques and contribute to real-world applications that enhance user engagement and experience through experimentation and data-driven decisions.
You will collaborate with senior researchers, engineers, and product teams to develop innovative models, contribute to research publications, and gain hands-on experience with A/B testing and evaluation of ML-driven features in a high-impact industry setting.
Job Responsibilities
Responsibilities include but are not limited to:
Research & Development:Conduct cutting-edge research in ML, focusing on personalization, recommendations, and NLP techniques (e.g., transformers, embeddings, reinforcement learning).Design, prototype, and evaluate ML models that drive personalized recommendations and improve user experiences across platforms.Stay up-to-date with the latest research, and contribute to internal research papers and presentations.Data Analysis, Modeling & Experimentation:Work with large-scale datasets to build, train, and optimize machine learning models.Develop and fine-tune models for improving recommendation accuracy and user personalization using collaborative filtering, content-based filtering, hybrid models, and deep learning techniques.Design, implement, and analyze A/B tests to evaluate the effectiveness of personalized recommendations and other ML-driven features.Interpret results from A/B tests to provide actionable insights for product teams and help iterate on model improvements.Collaboration & Communication:Collaborate with cross-functional teams, including data engineers, product managers, and senior researchers, to integrate research insights into production systems.Present research findings and A/B test results to both technical and non-technical stakeholders.
Preferred Skills
Strong background in machine learning, deep learning, and natural language processing.Familiarity with techniques in personalization and recommendation systems (e.g., matrix factorization, collaborative filtering, reinforcement learning).Experience with A/B testing frameworks, experimentation design, and analyzing experimental results.Proficiency in ML frameworks and tools such as TensorFlow, PyTorch, scikit-learn, etc.Proficient in Python and data analysis libraries (e.g., Pandas, NumPy).Experience working with large datasets and cloud-based platforms (e.g., Databricks, AWS, GCP) is a plus.Strong problem-solving skills and ability to work independently as well as in a collaborative environment.Published research papers in top-tier ML/NLP conferences or journals.Experience with transformer-based models (e.g., BERT, GPT) and advanced NLP techniques.Strong programming and software engineering skills for building scalable machine learning models.Experience working with A/B methodologies and designing complex experiments.Preferred Majors: Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
What You'll Gain
Hands-on experience working on impactful machine learning projects in personalization, recommendations, and NLP domains.Mentorship from experienced researchers and engineers in the field.The opportunity to work with A/B testing frameworks to evaluate the performance and business impact of your research.Potential to contribute to innovative products and publish in leading ML/NLP conferences.Networking opportunities within a fast-paced, research-driven company.Minimum Qualifications and Eligibility Requirements
Current PhD student in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.Available to work 40 hours per week over the course of the summer program- June 2 through August 15, 2025Authorized to work in the United StatesAvailable to report in-person to the work location on the job posting (unless virtual offering)Comcast is an Affirmative Action/EEO employer M/F/D/V
CompensationBase Pay: $55.00
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)
Relative Work Experience0-2 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.
Job SummaryThis job code is to be used for internships and co-ops. It is not to be used for temporary or contract workers.
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
The Content Discovery team is responsible for powering the search, browse, recommendations, personalization, and voice capabilities for our entertainment products.
Role Description
We are looking for a passionate and skilled PhD student to join our research team as a Machine Learning Research Intern. In this role, you will work on cutting-edge problems in the domains of personalization, recommendation systems, and natural language processing (NLP). This is an excellent opportunity for a PhD student to apply advanced machine learning (ML) techniques and contribute to real-world applications that enhance user engagement and experience through experimentation and data-driven decisions.
You will collaborate with senior researchers, engineers, and product teams to develop innovative models, contribute to research publications, and gain hands-on experience with A/B testing and evaluation of ML-driven features in a high-impact industry setting.
Job Responsibilities
Responsibilities include but are not limited to:
Research & Development:Conduct cutting-edge research in ML, focusing on personalization, recommendations, and NLP techniques (e.g., transformers, embeddings, reinforcement learning).Design, prototype, and evaluate ML models that drive personalized recommendations and improve user experiences across platforms.Stay up-to-date with the latest research, and contribute to internal research papers and presentations.Data Analysis, Modeling & Experimentation:Work with large-scale datasets to build, train, and optimize machine learning models.Develop and fine-tune models for improving recommendation accuracy and user personalization using collaborative filtering, content-based filtering, hybrid models, and deep learning techniques.Design, implement, and analyze A/B tests to evaluate the effectiveness of personalized recommendations and other ML-driven features.Interpret results from A/B tests to provide actionable insights for product teams and help iterate on model improvements.Collaboration & Communication:Collaborate with cross-functional teams, including data engineers, product managers, and senior researchers, to integrate research insights into production systems.Present research findings and A/B test results to both technical and non-technical stakeholders.
Preferred Skills
Strong background in machine learning, deep learning, and natural language processing.Familiarity with techniques in personalization and recommendation systems (e.g., matrix factorization, collaborative filtering, reinforcement learning).Experience with A/B testing frameworks, experimentation design, and analyzing experimental results.Proficiency in ML frameworks and tools such as TensorFlow, PyTorch, scikit-learn, etc.Proficient in Python and data analysis libraries (e.g., Pandas, NumPy).Experience working with large datasets and cloud-based platforms (e.g., Databricks, AWS, GCP) is a plus.Strong problem-solving skills and ability to work independently as well as in a collaborative environment.Published research papers in top-tier ML/NLP conferences or journals.Experience with transformer-based models (e.g., BERT, GPT) and advanced NLP techniques.Strong programming and software engineering skills for building scalable machine learning models.Experience working with A/B methodologies and designing complex experiments.Preferred Majors: Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
What You'll Gain
Hands-on experience working on impactful machine learning projects in personalization, recommendations, and NLP domains.Mentorship from experienced researchers and engineers in the field.The opportunity to work with A/B testing frameworks to evaluate the performance and business impact of your research.Potential to contribute to innovative products and publish in leading ML/NLP conferences.Networking opportunities within a fast-paced, research-driven company.Minimum Qualifications and Eligibility Requirements
Current PhD student in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.Available to work 40 hours per week over the course of the summer program- June 2 through August 15, 2025Authorized to work in the United StatesAvailable to report in-person to the work location on the job posting (unless virtual offering)Comcast is an Affirmative Action/EEO employer M/F/D/V
CompensationBase Pay: $55.00
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)
Relative Work Experience0-2 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.