Engineer 3, Machine Learning

Comcast brings together the best in media and technology. We drive innovation to create the world's best entertainment and online experiences. As a Fortune 50 leader, we set the pace in a variety of innovative and fascinating businesses and create career opportunities across a wide range of locations and disciplines. We are at the forefront of change and move at an amazing pace, thanks to our remarkable people, who bring cutting-edge products and services to life for millions of customers every day. If you share in our passion for teamwork, our vision to revolutionize industries and our goal to lead the future in media and technology, we want you to fast-forward your career at Comcast.

Job Summary

Responsible for developing and deploying machine learning algorithms. Evaluates accuracy and functionality of machine learning algorithms. Translates application requirements into machine learning problem statements. Analyzes and evaluates solutions both internally generated as well as third party supplied. Develops novel ways to use machine learning to solve problems and discover new products. Has in-depth experience, knowledge and skills in own discipline. Usually determines own work priorities. Acts as resource for colleagues with less experience.

Job Description

Position Summary

We are looking for a Machine Learning Engineer to join our team of ML practitioners and engineers passionate about solving high-impact personalization problems. This role is ideal for someone with a strong ML foundation, a love for clean, scalable code, and a desire to grow by owning and shipping production-ready models.

You will work with large-scale behavioural datasets, develop and evaluate recommendation and ranking models, and partner cross-functionally to deliver features that directly influence how millions of users interact with our platforms.

Key Responsibilities

• Model Development: Design, train, and optimize ML models for personalized ranking, search relevance, and engagement metrics.
• Data Analysis: Analyse large-scale behavioural/product datasets to guide model features and product strategies.
• Production Integration: Collaborate with senior engineers to ship models into production with performance and reliability in mind.
• Experimentation: Support A/B testing, fast iteration, and hypothesis-driven personalization improvements.
• Collaboration: Work closely with data scientists, product managers, and designers to turn business goals into ML-driven solutions.

Tech Stack: Machine Learning Engineer/ResearcherProgramming Languages

• Python

Machine Learning Frameworks

• PyTorch
• TensorFlow

Data Manipulation & Processing

• Pandas
• Apache Spark

ML Lifecycle & Workflow Tools

• MLflow
• Apache Airflow

Version Control

• Git

Conceptual/Algorithm Knowledge

• Supervised and unsupervised learning
• Generative models
• Ranking algorithms
• Basic statistics

Others

• A/B Testing and Experimentation
• Production integration and deployment of ML models
• Cross-functional collaboration (Product, UX, Engineering)

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 benefits summary on our careers site for more details.

Education

Bachelor's Degree

While possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience.

Certifications (if applicable)

Relevant Work Experience

5-7 Years

Comcast is 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.