Jobs at Tubi

Manage a portfolio of DSP, SSP, and ad tech partnerships, overseeing performance, communications, integrations, optimization, and growth initiatives. Collaborate with Partner Sales, Ad Operations, Product, and Marketing teams to launch and improve programmatic integrations. Analyze monetization metrics, develop pricing and inventory strategies, lead partner reviews, and create scalable reporting, processes, and partner-facing materials. The role requires strong programmatic advertising, publisher monetization, commercial judgment, analytical, communication, and stakeholder-management expertise.

Leads Tubi’s consumer and brand communications strategy, shaping narratives, earned-first campaigns, product storytelling, cultural participation, and media relationships. Partners with Brand, Product, Social, Content, research, analytics, finance, and agencies to create compelling stories, identify cultural opportunities, translate platform innovation for consumers, and measure impact beyond media impressions.

Leads communications operations by translating strategy into priorities, managing integrated calendars and cross-functional projects, establishing operating rhythms, tracking budgets and vendors, and improving systems, reporting, and organizational effectiveness. Partners with communications leadership and teams across marketing, content, product, ad sales, international, and corporate communications to coordinate launches, identify dependencies, and maintain continuity in a fast-moving environment.

Leads publicity strategy for Tubi Originals across movies, series, and creator-led content. Develops culturally relevant earned-media campaigns, manages talent and media relationships, advises executives and creators, oversees agencies, supports high-profile events, and mentors junior team members. Partners cross-functionally with Content, Creator, Brand, Social, Integrated Marketing, and International teams to generate attention beyond traditional entertainment publicity cycles.

Reviews advertising, promotional, and streaming content for compliance with Tubi policies, legal standards, industry guidelines, and ratings frameworks. Applies written policies consistently, evaluates advertiser-submitted claims, documents findings, recommends restrictions or removals, escalates policy issues, and collaborates with Legal, Sales, Ad Operations, Content, and producers. The role also analyzes industry practices, supports operational improvements, and requires a Wednesday-Sunday hybrid schedule with weekend work.

Leads Product Support Operations across technical program management and customer experience. Owns company-level programs, AI-enabled operating systems, customer support operations, planning cycles, executive reviews, and organizational communications. Develops teams, advises executives, manages portfolios, and personally builds agentic workflows and automation while coordinating complex initiatives across engineering, product, design, data science, finance, and external partners.

Supports digital advertising campaign execution from order booking through reporting. Responsibilities include validating orders, collecting and tracking creative assets, submitting trafficking requests, monitoring campaign delivery, escalating pacing risks, preparing client reports and presentation decks, and reconciling delivery for billing. The role coordinates with Account Management, Ad Operations, Sales, and Revenue Operations while maintaining accuracy across multiple concurrent campaigns.

Own the end-to-end performance improvement plan process, coach managers through difficult performance conversations, and partner with HRBPs on talent programs. Design initiatives that improve manager effectiveness, use workforce analytics to inform strategy, lead cross-functional performance efforts, and analyze intervention trends. The role requires balancing multiple PIPs and programs while ensuring fair, consistent, legally sound documentation and outcomes.

Lead ML engineering and infrastructure teams to design, build, and scale end-to-end ML systems (recommendation, personalization, ads), architect distributed low-latency serving and streaming platforms, oversee ML pipelines, ensure reliability, observability, cost efficiency, and partner with product and engineering to deliver ML-driven experiences.

The Machine Learning Engineer will design, develop, and implement advanced recommendation systems, collaborating with cross-functional teams to enhance personalization for a global audience.

Lead and manage the Content Acquisitions Legal team, advise on content licensing and partnerships, draft and negotiate content acquisition and distribution agreements, establish processes and templates, collaborate cross-functionally (Marketing, Product, Finance, Fox Legal), handle content-related legal issues (IP, DRM, privacy, sponsorships), train and support legal team members, and escalate material risks to the General Counsel.

Lead architecture and implementation of an AI-centric internal platform: design extraction pipelines, confidence scoring, cross-system aggregation, resilient interfaces, and production-grade ML integrations. Own complex subsystems, ship iteratively, validate accuracy, manage AI cost and human-in-loop controls, and raise engineering standards via reviews and technical guidance.

Lead day-to-day administration of advertising standards and brand safety across direct-sold, programmatic, sponsorship, and branded content. Advise on complex/high-risk ads, partner cross-functionally to implement policy, define scalable controls and tooling, use BI and AI-assisted review to monitor enforcement, and identify emerging risks and regulatory issues.

Lead creative strategy and execution for consumer and B2B campaigns, broadcast promos, event sizzles, and motion work. Manage concepting, briefs, and creative direction across design, animation, editorial, and sponsorship deliverables. Collaborate with producers and cross-functional teams to prioritize work, maintain quality, and drive AI adoption in creative workflows while presenting and influencing senior stakeholders.

The role involves designing scalable distributed systems using Scala, enhancing feature stores for performance, and collaborating with ML engineers to resolve challenges.

Apply machine learning, artificial intelligence, statistical analysis, and causal inference to large datasets and product analytics. Develop insights and recommendations for recommendation systems and user experiences. Evaluate experiments through planning, monitoring, and post-analysis, build data pipelines and tools, and communicate complex findings to stakeholders to support business decisions.