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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/Researcher
Programming Languages
Machine Learning Frameworks
Data Manipulation & Processing
ML Lifecycle & Workflow Tools
Version Control
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)
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.
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.
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.
Relevant Work Experience
5-7 Years
