Overview:

The Applied Machine Learning Group creates personalized streaming experiences. These experiences do more than just provide recommendations. They transform how audiences find, interact with, and enjoy content on Paramount+ and Pluto TV. We offer real-time discovery and personalized participation. We improve viewing experiences with advanced short-form and interactive content. This is possible because of our deep audience insights, understanding of different content types, and advanced machine learning. Our work directly connects millions of viewers to the stories they love while leading meaningful business impact for Paramount Streaming.

We are looking for a Senior Director of Technical Product Management. This person will be in charge of product strategy and execution for our ML platform and infrastructure. The platform allows for personalization. It provides content intelligence. It also offers AI-driven streaming experiences. These features are designed for Paramount's global ecosystem.

This leader will set the vision and plan for key ML platform features. These features include model training, evaluation, lifecycle management, and serving models in both real-time and batch formats. They will also manage feature stores, data pipelines, and ML data platforms. Additionally, they will oversee runtime systems and integrations. Their focus will be on developer tools and ensuring that AI systems are reliable, scalable, low-latency, and cost-efficient.

This is a highly strategic and deeply technical leadership role. You will partner closely with engineering, data science, product, and executive management to ensure our ML platform enables rapid innovation, production-grade reliability, and proficient global scale. The role is responsible not only for how ML systems are built and operated, but for how platform capabilities accelerate the future of AI across Paramount Streaming.

Primary Responsibilities:

Strategy & Vision

• Define and lead the strategy for our ML platform and infrastructure. This plan will span multiple years. It will support personalization, discovery, content intelligence, and new AI-driven streaming experiences.
• Translate company objectives into scalable platform investments with clear reliability, performance, developer velocity, and cost outcomes
• Identify new capabilities for the machine learning platform. This includes real-time inference. It also covers enabling foundation models, multimodal systems, and hybrid AI architectures.
• Represent ML platform strategy at the executive and cross-company level
• Balance long-term platform investment with near-term product acceleration and measurable business impact

Technical Product Leadership

• Lead product strategy for end-to-end ML lifecycle capabilities, including training, deployment, monitoring, iteration, and model governance
• Drive roadmap and prioritization for real-time and batch inference infrastructure
• Lead product direction for feature stores, ML data platforms, data pipelines, and offline/online consistency frameworks
• Enable experimentation platforms, model evaluation workflows, and safe rollout practices for AI and ML systems
• We aim to improve developer productivity. We will do this using platform APIs, tools, abstractions, documentation, and self-service capabilities.
• Partner with ML, platform, data, and cloud engineering teams to build scalable, reliable, secure, and cost-efficient AI systems
• Drive alignment between research innovation, platform capabilities, production readiness, and business outcomes
• Ensure platform decisions improve personalization. They should also aid in content intelligence, search, short-form content, experimentation, and future AI-powered product experiences.

Organizational Leadership

• Lead, mentor, and grow a team of technical product managers
• Establish operating rhythms, product standards, roadmap governance, and clear prioritization frameworks
• Foster a data-driven, experimentation-first culture across product, engineering, data science, and analytics teams
• Influence roadmaps for different teams. These teams include personalization, UX, growth, marketing, content strategy, and platform engineering.
• Build effective partnerships across matrixed global organizations and help teams operate from a shared technical and product strategy

Measurement & Business Impact

• Define and track north-star metrics for ML platform success, including:
• Model deployment velocity
• System reliability, latency, and availability
• Infrastructure cost efficiency
• Developer productivity and platform adoption
• Time from model development to production impact
• Ensure good visibility. Focus on safety during experiments. Monitor the models. Keep high operational standards.
• Translate platform performance, telemetry, and developer feedback into clear product direction
• Communicate technical strategy, tradeoffs, platform health, and business impact clearly to executive stakeholders

Industry Leadership

• Stay at the forefront of large-scale machine learning platforms. Focus on MLOps, real-time inference, and distributed model serving. Work with infrastructure for foundation models, multimodal AI systems, and cloud-native AI architectures.
• Bring external perspective and best practices from leading consumer technology, streaming, cloud, and AI-driven organizations
• Help shape how Paramount Streaming builds, scales, and operates the technical foundations for applied AI

Basic Qualifications:

• 10+ years of experience in product management, technical product management, or equivalent product executive team roles
• 5+ years leading ML platform, infrastructure, MLOps, data platform, or AI-driven systems
• Experience leading PMs or leading complex platform product areas across multiple engineering and science teams
• Experience delivering large-scale machine learning platforms. This includes distributed AI infrastructure, data platforms, or developer platforms. Relevant industries are streaming, consumer technology, cloud platforms, or AI-first companies.
• Technical fluency across ML lifecycle systems, data infrastructure, distributed systems, model serving, and production AI architectures
• Experience with real-time and batch inference architectures. Knowledge of feature stores, data consistency, and scalability. Understand reliability. Understand cost optimization.
• Experience with MLOps platforms, orchestration, CI/CD for ML, model observability, drift detection, and safe deployment practices
• Fluency with data analysis workflows, including SQL, Python, telemetry, experimentation data, and platform health metrics
• Executive communication skills, with the ability to translate technical platform work into business impact, strategic tradeoffs, and clear decision-making
• Proven ability to align engineering, data science, infrastructure, product, and business stakeholders across matrixed organizations

Preferred Qualifications:

• Experience in building or improving machine learning platforms. This includes skills in personalization, recommendations, search, content intelligence, advertising, or other large consumer AI systems.
• Experience with real-time personalization systems. Experience with online feature serving. Experience with model serving infrastructure. Experience with experimentation platforms. Experience with decisioning systems.
• You should understand foundation model infrastructure and multimodal AI systems. It is also important to have experience with vector pipelines, embeddings, and new AI application architectures.
• Experience balancing platform reliability, developer velocity, infrastructure cost, and product impact at global scale
• Hands-on technical fluency with coding tools such as Python, SQL, IDEs, GitHub, notebooks, dashboards, and developer workflows
• Experience using AI-assisted development tools such as Claude Code, Gemini for developers, Cursor, or similar tools to accelerate prototyping and technical investigation
• Ability to individually create, evaluate, or demonstrate basic proofs of concept for ML platform, recommendation, personalization, or AI infrastructure ideas
• Understand how internal developer platforms function. Focus on adoption and usability. Promote self-service workflows. Ensure the documentation and design of platform APIs are clear.
• Affinity for building the technical foundations that power the future of streaming, personalization, and AI-driven entertainment

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: $203,000.00 - 255,000.00.

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 Agreement. This position is bonus eligible.

What We Offer:

• Attractive compensation and comprehensive benefits packages. Check out our full list of benefits here: https://www.paramount.com/careers/benefits
• Generous paid time off.
• An exciting and fulfilling opportunity to be part of one of Paramount's most dynamic teams.
• Opportunities for both on-site and virtual engagement events.
• Unique opportunities to make meaningful connections and build a vibrant community, both inside and outside the workplace.
• Explore life at Paramount: https://www.paramount.com/careers/life-at-paramount