Principal Machine Learning Engineer – Presentation and Visual Optimization

Job not on LinkedIn

🕒 May 6

🗽 New York – Remote

🗽 New York – Remote

💵 $234k - $250k / year

⏰ Full Time

🔴 Lead

🤖 Machine Learning Engineer

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Paramount

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1912

💼 Consulting

📣 Marketing

📱 Media

Consulting • Marketing • Media

Paramount is a global multimedia entertainment and news company that offers a range of services including direct-to-consumer digital subscription video on-demand and live streaming through Paramount+. It also owns Pluto TV, a leading free streaming television service, MTV, the world’s premier youth entertainment brand, and CBS Sports, a leader in television sports broadcasts. Paramount Pictures, since 1912, has been a legendary producer and distributor of films, hosting a library of over 1,000 titles. The company is deeply committed to inclusion and impact, focusing on diversity, global sustainability, and content that affects change. Being a significant player in both live and on-demand streaming services, Paramount embraces a wide array of content from sports to kids’ entertainment, comedy, and groundbreaking documentaries, impacting both linear and streaming platforms globally.

📋 Description

• Lead the Presentation Pod: Define the technical roadmap for visual personalization, bridging the gap between ML science and UI/UX design. • Artwork & Marquee Personalization: Architect and deploy multi-armed bandit (MAB) systems to dynamically select the best creative assets for show tiles and hero marquees. • Layout & Style Optimization: Develop models to personalize carousel design types (e.g., square vs. poster), presentation styles, and even the ordering of attributes shown to the user. • Title & Copy Optimization: Utilize NLP and LLMs to experiment with and optimize carousel titles and content descriptions based on user preferences and trending topics. • Fast Experimentation Frameworks: Design "always-on" experimentation pipelines that can shift traffic based on model confidence and reward signals (CTR, Playback Start). • Visual Understanding: Partner with Content Engineering to leverage visual embeddings and computer vision signals to understand why certain artwork performs better than others.

🎯 Requirements

• 6-8+ years of experience in machine learning engineering or applied science. • Deep hands-on experience with Multi-Armed Bandits, Contextual Bandits, Thompson Sampling, or Upper Confidence Bound (UCB) algorithms. • Proven track record of designing high-velocity A/B testing or online learning systems. • Proficiency in Python, PyTorch/TensorFlow , and big-data processing (Spark/Databricks). • Experience leading a technical pod or team, with a focus on translating product/design needs into engineering requirements. • Experience in Visual Personalization (artwork, thumbnails, or creative optimization). • Background in Computer Vision (OCR, aesthetic scoring, or image feature extraction). • Knowledge of Reinforcement Learning (RL) for sequential layout optimization. • Familiarity with LLMs/Generative AI for automated copy generation and title testing.

🏖️ Benefits

• medical • dental • vision • 401(k) plan • life insurance coverage • disability benefits • tuition assistance program • PTO