Senior Director, Technical Product Management - ML Platform & Infrastructure

#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:   #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 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 readine