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45518

Technology

New York

Full-Time

Fully Remote

#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 thepowerto 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:

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 enthusiastic people who not only recognize the power of content but also enjoy a touch of fun and uniqueness. Collectively, we co-create moments that matter – both for our audiences and our employees – and aim to leave a positive mark on culture.

The Applied Machine Learning Group creates personalized streaming experiences. These experiences include more than just recommendations. They influence how audiences find, interact with, and enjoy content on Paramount+ and Pluto TV. We evaluate audience insights and understand content in various formats. We also use advanced machine learning. This allows us to support real-time discovery, create personalized interactions, and develop innovative short-form and interactive viewing experiences. Our work directly connects millions of viewers to the stories they love while spearheading meaningful business impact for Paramount Streaming.

We are looking for a Senior Director of Technical Product Management. This person will lead the product strategy and execution. They will also guide the direction of Content Engineering & Intelligence. This will be within Paramount’s global streaming ecosystem.

This leader will guide the vision and strategy for important content systems. They will focus on improving metadata quality and content knowledge. They will also manage the creation of embedding generation, short-form content workflows, and reusable content services for Paramount+ and Pluto TV.

This role covers several areas. It includes content metadata and feature pipelines. It also involves content data engineering, canonical content systems, and embedding and enrichment pipelines. Additionally, this role focuses on short-form content engineering workflows and machine learning capabilities. The main emphasis is on content services platforms. It aims to enhance internal user experiences and improve platform features for discovery, personalization, search, experimentation, and new AI-powered content experiences.

You will work closely with several teams, including content engineering, applied ML, platform engineering, data science, product, design, operations, and the executive team. Your goal is to ensure our content foundations are scalable and reliable. They must also support the next generation of AI-driven streaming experiences.

This is a highly strategic and deeply technical executive role responsible not only for what content systems are built, but for how content becomes a durable strategic asset across Paramount Streaming.

Primary Responsibilities:

Define and lead the multi-year product strategy for Content Engineering & Intelligence across Paramount+ and Pluto TV

Turn company goals into scalable investments. Concentrate on metadata, content comprehension, embeddings, short-form systems, and content services.

Identify and develop new content capabilities. These capabilities include multimodal enrichment, automated tagging, and content graph evolution. They also involve short-form asset generation and reusable content services for both internal and platform-facing uses.

Represent Content Engineering & Intelligence strategy at the executive and cross-company level

Balance long-term platform investment with near-term delivery needs and measurable business impact

Technical Product Leadership

Lead product strategy for content metadata architecture, modeling, and lifecycle management

Guide product direction for feature pipelines, enrichment workflows, canonical content data systems, and internal content services

Lead product planning for embedding generation, vector pipelines, and ML-ready content datasets

Create short-form content engineering pipelines. Develop tools and machine learning capabilities. These tools should help with content comprehension, transformation, and improvement.

Improve internal tooling and user experiences for teams that create, manage, validate, and operationalize content intelligence

Partner with engineering and ML teams to build scalable, reliable, and cost-efficient content systems

Align the content infrastructure with its uses. This involves several activities. These activities involve several key areas. They include discovery and ranking. They also cover search, personalization, experimentation, and improving the consumer experience.

Ensure platform APIs and internal workflows are designed for adoption, usability, and scale

Organizational Leadership

Lead, mentor, and grow a team of technical product managers

Establish operating rhythms and product standards. Create guidelines for the plan. Set clear prioritization frameworks across Content Engineering and Intelligence.

Foster a platform mindset focused on reuse, quality, documentation, operational excellence, and measurable business leverage

Influence roadmaps across personalization, search, editorial, growth, content operations, design, and AI/ML teams

Help content engineering, applied ML, and product teams operate as a unified system rather than a collection of siloed capabilities

Measurement & Business Impact

Define and track north-star metrics for Content Engineering & Intelligence success, including:

Metadata completeness, quality, and freshness

Pipeline reliability, latency, and operational efficiency

Coverage and quality of content embeddings and enrichment

Adoption and usability of content services and internal tools

Pace of onboarding new content capabilities and surfaces

This considers how discovery and personalization are affected. It also covers short-form involvement and experimentation.

Ensure content systems are measurable, observable, and tied to downstream business impact

Translate system health, coverage, quality signals, and workflow pain points into clear product direction

Communicate platform impact, business outcomes, and technical tradeoffs clearly to executive stakeholders

Industry Leadership

Stay updated on metadata systems and knowledge representation. Focus on multimodal AI and content knowledge. Work with embeddings and vector pipelines. Manage short workflows and internal tools. Oversee streaming infrastructure and modernize the media supply chain.

Bring external perspective and best practices from leading streaming, media, consumer technology, and AI-driven companies

Help shape how Paramount Streaming builds, scales, and applies content intelligence across future AI-driven experiences

Basic Qualifications:

10+ years of experience in product management, technical product management, or equivalent product executive team roles

5+ years leading technical product areas in content platforms, metadata systems, AI/ML infrastructure, content intelligence, data platforms, or adjacent domains

Experience leading PMs or complex technical product areas across engineering, ML, data, design, operations, and business teams

Have experience in delivering large content platforms. This includes metadata systems, internal tools, data platforms, and machine learning systems. You should have this experience in streaming, media, consumer technology, or AI-focused companies.

Technical fluency across data systems, content pipelines, APIs, internal tools, metadata systems, and ML-enabled platforms

Experience with content metadata systems. Knowledge of enrichment workflows and canonical metadata models. Knowledge of content identifiers, taxonomy, ontology, and content normalization methods.

Experience with data pipelines. Experience with feature stores. Experience with datasets that are ready for models. Experience with batch and near-real-time architectures. Knowledge of MLOps, monitoring, and experimentation systems.

Fluency with data analysis workflows, including SQL, Python, telemetry, data quality signals, instrumentation, and platform health metrics

Executive communication skills, with the ability to translate technical platform work into business impact, strategic tradeoffs, and clear decision-making

Ability to align engineering, ML, design, operations, product, and business stakeholders across matrixed organizations

Preferred Qualifications:

Experience in building or improving content intelligence capabilities. This includes personalization and recommendations. It also involves search, short-form content, content discovery, and advertising. It also involves working with other large-scale consumer AI systems.

Familiarity with embedding generation, vector-based content representation, vector databases, asset-level and title-level content intelligence systems, and downstream ML readiness

Experience with applied ML systems used in content transformation, understanding , tagging, enrichment, short-form generation, or