Senior Machine Learning Engineer, Short-form

#WeAreParamount on a mission to unleash the power of content… you in?
We’ve got the brands, we’ve got the stars, we’ve got the power to achieve our mission to entertain the planet – now all we’re missing is… YOU! Becoming a part of Paramount means joining a team of passionate people who not only recognize the power of content but also enjoy a touch of fun and uniqueness. Together, we co-create moments that matter – both for our audiences and our employees – and aim to leave a positive mark on culture.

 

 

Overview

 

 

We are looking for a Senior Machine Learning Engineer to join the Shortform pod.

 

Your mission is the Personalization of Short-form experiences, specifically optimizing the "in-view" and "in-carousel" experiences. As we expand our "Gist" and clip ecosystem, you will lead the design of models that determine which short-form asset will most effectively convert a casual browser into a committed viewer.

 

This is a Senior role, meaning you are trusted to define the technical approach for complex ranking and selection features. You will work within a GCP-based environment,

utilizing TensorFlow and PyTorch, with a heavy focus on Post-training RL (Reinforcement Learning) to optimize for long-term user satisfaction and session-level rewards.

 

 

Why This Role Matters

 

• Capturing Attention: You own the algorithms that select the right 30-second "hook" to show a user, directly impacting Click-Through Rate (CTR) and discovery velocity.
• Beyond the Click: By applying Post-training RL, you ensure that our short-form content drives meaningful long-term retention, not just short-term engagement.
• System Quality: You raise the bar for the Shortform pod by anticipating data risks and building highly reliable, multi-stage ranking pipelines.

 

 

Key Responsibilities

 

• Lead Feature Design: Own the end-to-end design of ranking models for in-view short-form content.
• Apply RL in Production: Implement Post-training RL techniques to align model outputs with complex user satisfaction metrics.
• Optimize for Scale: Build and maintain high-throughput pipelines in GCP using TensorFlow/PyTorch.
• Mentorship: Provide technical guidance to IC1-IC2 engineers on the pod, ensuring high standards for code and experimentation.
• Mitigate Risk: Identify and tackle systemic biases in how short-form content is surfaced to avoid "filter bubbles."

 

 

Basic Qualifications

 

• 5+ years of experience in MLE; proficient background in Reinforcement Learning; proficiency in GCP, TensorFlow, and PyTorch.

 

 

Additional Qualifications

 

• Experience in video-first social or streaming apps; background in multi-modal signal processing.

 

 

#LI-PG1

 

Paramount Streaming, a division within Paramount Global, is the home to the company's direct-to-consumer services spanning free and paid in the form of Pluto TV and Paramount+. Pluto TV is the global leader in free ad-supported TV, delivering more than 1,400 global channels and an extensive library of streaming content, including live and original channels. Paramount+, digital subscription video-on-demand and live streaming service, combines live sports, breaking news, and A Mountain of Entertainment™. Paramount+ features an expansive library of original series, hit shows and popular movies across every genre from world-renowned brands and production studios, including SHOWTIME®.

 

 

ADDITIONAL INFORMATION

 

Hiring Salary Range: $139,000.00 - 180,000.00. 

 

The hiring salary range for this position applies to New York, California, Colorado, Washington state, and most other geographies. Starting pay for the successful applicant depends on a variety of job-related factors, including but not limited to geographic location, market demands, experience, training, and education.  The benefits available for this position include medical, dental, vision, 401(k) plan, life insurance coverage, disability benefits, tuition assistance program and PTO or, if applicable,  as otherwise dictated by the appropriate Collective Bargaining Agreeme