Machine Learning Engineer, Personalization & Recommendation Systems

Comcast

3d • $142,651 - $213,977

About The Position

Join our Personalization team and help shape the future of customer experiences for millions of users across Comcast and Sky. We are looking for a Machine Learning Engineer with deep expertise in personalization and recommendation systems. This is an opportunity to work on cutting-edge algorithms, large-scale data systems, and deliver impactful solutions that drive engagement and satisfaction.

Requirements

• Ph.D. in Computer Science, Machine Learning, Statistics, or related field (or equivalent research experience).
• Strong background in machine learning, deep learning, and recommendation systems.
• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, etc.).
• Experience with large-scale data processing (Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
• Solid understanding of algorithms, data structures, and software engineering principles.

Nice To Haves

• Experience with personalization systems in media, e-commerce, or streaming platforms.
• Publications in top-tier ML conferences or journals.
• Experience applying contrastive learning techniques to improve model representations and performance.
• Strong understanding of large language models (LLMs) and hands-on experience with fine-tuning for domain adaptation.
• Ability to design and implement advanced sampling strategies for machine learning tasks.
• Proven track record of working on personalization and recommendation systems at scale.
• Familiarity with evaluation methodologies across multiple domains and optimizing models for cross-domain generalization.
• Familiarity with reinforcement learning or multi-armed bandit approaches.

Responsibilities

• Design, develop, and deploy machine learning models for personalization at scale.
• Leverage contrastive learning and large language models (LLMs) to improve content recommendations.
• Contribute to research-driven innovation, such as developing advanced sampling strategies and fine-tuning LLMs for cross-domain performance improvements.
• Research and implement state-of-the-art algorithms in recommendation systems, NLP, and predictive modeling.
• Collaborate with data scientists, engineers, and product teams to integrate models into production systems.
• Optimize model performance and ensure scalability across large datasets.
• Stay current with advancements in ML and personalization technologies.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees