Principal Machine Learning Engineer, Session and In-Player Experience

🕒 April 21

🗽 New York – Remote

🗽 New York – Remote

💵 $234k - $250k / year

⏰ Full Time

🔴 Lead

🤖 Machine Learning Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

Apply Now

Find Similar Remote Jobs

Receive Emails For Remote Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Paramount

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1912

📱 Media

👥 B2C

Media • B2C • Entertainment

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 Multi-Stage Personalization: Design and deploy retrieval and deep ranking systems specifically optimized for in-player surfaces and "Watch-Next" carousels. • Own the Session Lifecycle: Develop end-to-end ML pipelines that utilize session-based modeling and real-time user behavior to predict the next best piece of content. • Optimize for Performance: Architect systems that meet strict latency requirements necessary for in-player experiences where delays directly impact the viewing experience. • Cross-Functional Strategy: Partner with Product, Design, and Content teams to define success metrics specific to session length, "binge" rates, and playback transitions. • Scientific Rigor: Establish high-integrity experimentation practices and improve offline→online correlation for session-based rewards and contextual bandits. • Technical Mentorship: Act as a player-coach, developing technical talent within the pod and shaping the culture of the broader AMLG.

🎯 Requirements

• 6–8+ years of experience in machine learning engineering, recommender systems, or large-scale ranking. • Demonstrated success deploying ML systems in high-traffic, low-latency production environments. • Deep knowledge of session modeling, representation learning, and contextual bandits. • Experience leading and mentoring senior technical teams with the ability to drive strategy while remaining hands-on. • Proficiency with modern ML frameworks (PyTorch, TensorFlow) and big-data ecosystems (Spark, Beam, Databricks).

🏖️ Benefits

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