Paramount
Paramount is a leading global media and entertainment company that creates premium content and experiences for audiences worldwide. Driven by iconic consumer brands, its portfolio includes CBS, Showtime Networks, Paramount Pictures, Nickelodeon, MTV, Comedy Central, BET, Paramount+, Pluto TV, among others. The company delivers the largest share of the U.S. television audience and boasts one of the industry’s most important and extensive libraries of TV and film titles. In addition to offering innovative streaming services and digital video products, Paramount provides powerful capabilities in production, distribution and advertising solutions for partners on five continents.
Overview & Responsibilities:
The Applied Machine Learning Group is looking for a Senior Technical Product Manager to drive the evolution of personalization and recommendation services for Paramount+ and Pluto TV! We are looking for someone to partner closely with data scientists, machine learning engineers, product partners, and cross-functional teams to build intelligent, data-driven products and experiences that improve content discovery and engagement.
You will be responsible for defining and driving our personalization roadmap, leading experimentation strategies, and ensuring that our recommendations driven by AI deliver value across a global user base. We are searching for someone who is passionate about machine learning, A/B testing, and streaming UX to build the future of how millions of users discover content!
Responsibilities:
Collaborate on product vision and roadmaps for personalization, focusing on recommendation models, ranking systems and tailored user experiences
Collaborate with ML engineers and data scientists to improve recommendation quality and optimize content discovery
Collaborate with other engineering and product partners to ensure that personalization features are intuitive, scalable, and drive engagement
Define and track key personalization metrics
Drive experimentation at scale, implementing A/B testing frameworks to measure the impact of personalization changes
Work with cross-functional teams (engineering, design, business, content) to identify and complete opportunities that improve the streaming experience
Conduct competitive research and stay on top of industry trends in recommendations motivated by AI, user behavior modeling and content personalization
Required Areas of Expertise:
Machine Learning Fundamentals
Proven understanding of personalization and recommender systems, including collaborative filtering, content-based filtering, and deep learning models
Knowledge of evaluation metrics and personalized engagement metrics
Awareness of bias mitigation and AI fairness in personalization models
AI/ML Infrastructure & Engineering
Familiarity with ML model development lifecycles, including training, deployment, and monitoring
Experience with real-time vs. batch personalization trade-offs (bandits, reinforcement learning, batch model retraining)
Understanding MLOps, data pipelines, and APIs for AI-powered applications
Data & Experimentation
Strong background in A/B testing, experimentation frameworks, and statistical significance
Experience analyzing data using SQL, Python, or visualization tools
Understanding of multi-armed bandits, reinforcement learning, and exploration/exploitation strategies
Product Strategy & Business Impact
Ability to prioritize AI/ML initiatives based on business impact and technical feasibility
Experience defining key performance indicators for AI informed personalization, balancing engagement, and retention
Communication & Cross-Functional Collaboration
Strong ability to translate technical ML concepts into business-friendly insights
Ability to collaborate with machine learning, data engineering, measurement ops, UX, and marketing teams to implement AI centric features
Skilled in executive storytelling to advocate for personalization initiatives
Basic Qualifications:
5+ years of product management experience, with at least 3+ years working on AI focused personalization or ML-based products
Deep understanding of A/B testing, experimentation platforms, and statistical analysis
Additional Qualifications:
Knowledge of streaming services and content discovery challenges in SVOD, AVOD, and hybrid models
Strong analytical mentality, with experience in SQL, data visualization tools, or experimentation platforms
