The Cape Surface in Toronto

About the Role: The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding and ads optimization that shape the future of streaming. We are seeking a highly skilled Senior Machine Learning Engineer to contribute to transformative projects in video personalization. In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy. As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross-functional teams to develop and optimize machine learning-driven solutions. This is a hybrid role in our Toronto office. What You'll Do: Design, develop, and implement recommendation systems and algorithms for a global audience Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences. Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement Your Background: 3+ years of industry experience building production Machine Learning systems BS, MSc, or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks Proficiency in building and deploying full-stack machine learning pipelines: data e

About the Role: Join us in shaping the future of streaming. Tubi is a free, ad-supported streaming service with a mission to make entertainment accessible to everyone. We serve millions of viewers with a massive library of movies, TV shows, live channels, and personalized recommendations, all without a subscription. As streaming continues to evolve, Tubi is building the technology, product experiences, and platform capabilities that help people discover and enjoy content effortlessly across every screen. If you’re excited by consumer-scale mobile engineering, high-quality user experiences, and the opportunity to impact how millions of people watch entertainment, we’d love to meet you. This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week. About the team: The Android team at Tubi builds the app experience that millions of users rely on to discover, browse, and watch content. We care deeply about performance, stability, accessibility, and thoughtful product execution. Our work spans core playback experiences, content discovery, personalization, onboarding, advertising experiences, and the mobile platform foundations that help teams ship quickly and safely. As a Senior Android Engineer, you will design, build, and deliver high-quality product features for Tubi’s Android app. You’ll work closely with Product, Design, Backend Engineering, QA, Data, and other client teams to create intuitive, reliable, and scalable mobile experiences. You’ll also help guide technical direction, improve engineering standards, mentor other engineers, and contribute to the long-term health of our Android codebase. This is a role for someone who enjoys building polished consumer products, solving complex technical problems, and raising the bar for Android engineering. What you’ll do Build elegant, performant, and reliable Android experiences using Kotlin and modern Android development practices Lead the full l

About the Role: Tubi is creating a Performance Partner role to focus on supporting managers end-to-end in developing and managing their teams. This role will own the end-to-end Performance Improvement Plan (PIP) process, partner closely with HRBPs to develop and execute strategic talent programs, and drive manager effectiveness across the organization. This is a highly visible role that sits at the intersection of performance management, talent strategy, and manager enablement — ideal for someone who wants to build and own a program from the ground up. This is an individual contributor role reporting to our VP of People. This role will be hybrid and can be based in SF/NYC/LA/Toronto. What You'll Do: Own the end-to-end Performance Improvement Plan (PIP) process — from initial documentation through execution, check-ins, and resolution — partnering with legal, managers and business leaders throughout Partner with HRBPs on HR programs for their teams (e.g., performance reviews, onboarding, promotions), bringing performance management expertise into broader talent initiatives Develop and execute strategic talent programs that drive manager effectiveness, bringing workforce trends and analytics into program design Advise managers on trade-offs when navigating complex, undefined performance issues; encourage experimentation and iteration in how managers approach team development Lead multi-team efforts related to performance and manager effectiveness (e.g., a performance refresh, a new PIP framework rollout), building trust and credibility across functions Balance competing demands across multiple concurrent PIPs and programs, orchestrating initiatives to deliver business-ready outcomes Coach managers directly on how to have difficult performance conversations, set clear expectations, and document performance issues appropriately Track and analyze trends across PIPs and performance interventions, sharing insights with HRBPs and People leadership to inform broader talent st

About the Role: The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding and ads optimization that shape the future of streaming. We are seeking a highly skilled Staff Machine Learning Engineer to contribute to transformative projects in video personalization. In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy. As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross-functional teams to develop and optimize machine learning-driven solutions. This is a hybrid role in our Toronto office. What You'll Do: Lead the design, development, and implementation of advanced recommendation systems and algorithms for a global audience Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences. Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement Your Background: 8+ years of industry experience building production Machine Learning systems MSc or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks Proficiency in building and deploying full-stack machine le

About the Role: Tubi's content platform is the engine behind one of the largest free streaming services in the world. Every play, every deal, every creator, every frame of video flows through systems CPE owns, and the surface area is enormous. Distributed services running on the hottest path of Tubi's traffic. Video pipelines processing one of the largest workloads in streaming. Workflow engines automating the operations that used to consume entire teams. Creator-facing products turning a back-office process into a real platform. And on top of all of it, an AI-native rebuild of the CMS that most companies aren't willing to attempt. This isn't a single-domain role. It's a platform where backend, frontend, video, infrastructure, and applied AI all collide at the scale where decisions actually matter, where an architectural choice ripples across millions of titles and billions of requests, and where the difference between "good enough" and "great" shows up in revenue. We're looking for builders who want to range across domains — backend one quarter, frontend the next, applied AI the one after that — and who want their work to be felt: by viewers when a title plays instantly, by creators when they go live the same day, by Content Ops when a workflow runs itself, and by the business when the platform stops being a cost center and starts being a force multiplier. The infrastructure is already there. The mandate is already there. What's missing is the people who want to build the thing, not talk about it. Come build it. This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week. What You'll Do: You'll work on systems that sit at the heart of Tubi's business, where the content pipeline meets the viewer, the creator, and increasingly, the AI agent. The work spans the full stack of a modern content platform: distributed services, video infrastructure, workflow automation, and applied AI, all running at

About the Role: The team is responsible for building and optimizing the UI/UX across all Web and OTT applications at Tubi. The team primarily focuses on implementing features related to user acquisition and growth, including but not limited to user registration, onboarding, SEO, and account management. As part of this team, you will work closely with Product and Design to develop cutting-edge, experiment-driven features that enhance the user experience. In addition to front-end development, you’ll be responsible for building the underlying technical architecture to ensure performance and scalability, while proactively exploring engineering-driven features and experiments that can drive user growth. You will be working with React, Node.js, GitHub Actions, Terraform, and CDN infrastructure to build and deploy high-performance applications that reach millions of users. This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week. What You'll Do: Work with product management and other stakeholders (Backend, Product, and UI/UX) to iterate on new growth-related features, including registration, onboarding, and SEO. Lead the technical architecture and implementation of scalable and resilient applications that run on multiple platforms, such as web, mobile web, and smart TV devices. Lead and drive innovation in building experiment-driven features that push the boundaries of user experience in streaming. Consistently ship features and improvements across Web and OTT apps with minimal guidance, collaborating with cross-functional teams to deliver high-impact updates. Identify and implement improvements in shared UI components, platform-specific optimizations, and overall front-end infrastructure. Take ownership of the codebase and proactively identify opportunities for refactoring and development process improvement. Mentor and collaborate with fellow engineers, sharing technical expertise and contributi

About the Role: Tubi is seeking a highly skilled and experienced QA Automation Engineer to lead quality assurance initiatives for our cutting-edge streaming and AI-driven product features. This pivotal role involves ensuring exceptional end-to-end user experiences, robust streaming playback, and the accuracy and integrity of our AI/ML features across web, mobile, and OTT platforms. We're looking for a candidate with a strong background in streaming QA and deep technical knowledge of media workflows. You'll be instrumental in collaborating with engineering, product, and data science teams to define comprehensive QA strategies that guarantee both functional excellence and data-level quality This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week. What You'll Do: Design and lead test strategies for streaming workflows, playback systems, and AI-powered features. Test across platforms (web, mobile, and connected TV) to ensure functional parity and playback stability. Validate streaming performance—including ABR logic, encoding pipelines, and DRM integrations—under diverse real-world conditions. Debug with precision using tools like Charles Proxy, Chrome DevTools, ADB, and Xcode. Collaborate with data and ML teams to validate AI model updates, recommendations, and personalization accuracy. Leverage AI-assisted QA tools to enhance regression coverage, UI validation, and anomaly detection. Contribute to automation and CI/CD frameworks, driving faster, more reliable releases. Oversee QA deliverables for multiple concurrent releases and ensure seamless sign-off for production launches. Monitor live environments for playback or recommendation anomalies post-release and escalate issues promptly. Continuously improve QA processes, metrics, and reporting for streaming and AI validation. Your Background: Bachelor’s degree in Computer Science, Software Engineering, or related field, or equivalent hands-on experi

About the Role: As a Staff Software Engineer on the ML Infrastructure team, you will collaborate closely with the Machine Learning and Product teams to build world-class machine learning inference platforms. These platforms power essential services like personalized recommendations, search, and content understanding across Tubi. A core responsibility of this team is developing and maintaining low-latency ML model serving systems that support Deep Learning, LLM, and Search models. This involves building self-service infrastructure and critical components such as the inference engine, feature store, vector store, and experimentation engine. You will improve the way we deploy and operate our services and even contribute to open-source projects. This role grants the architectural freedom to explore new frameworks, lead critical cross-functional projects, and transform the capabilities of our ML and Product teams. Responsibilities: Design and build scalable, high throughput, and low latency distributed systems using Scala Build reusable components and services that serve various ML applications like Personalization, Search, Ads and Exploration Partner closely with ML engineers to understand their challenges and limitations and develop scalable solutions to address them. Proactively recommend solutions to keep our ML Inference stack state of the art. Take a data driven approach to identifying & optimizing latency, cost, and efficiency of our infra. Lead large scale cross functional refactorings if necessary Mentor other engineers on the team on system design, effective incident management, interviewing, leveraging LLMs for work, etc. Collaborate with ML, Product, and cross functional engineering teams to define the long term vision and architecture for ML Infrastructure at Tubi. Your Background: Experience designing and building scalable, distributed systems in any modern backend language (e.g., Scala, Java, Python, Go, C++); experience with Scala or JVM b

About the Role: As Sr Manager, Creator & Content Partnerships - Canada, you'll lead Tubi’s effort to source, grow, and manage relationships with Canadian creators. You will support the GM Tubi Canada, in expanding relationships with content partners. You will play a pivotal role in scaling and evolving our Canadian content proposition, helping to shape the broader Canadian content strategy, and contributing to the global Tubi for Creators initiative. This is a hands-on, high impact role that blends business development, partnership management, and strategic, data-led thinking. This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week. What You'll Do: Source, pitch, and secure partnerships with Canadian creators, working directly with creators, talent agencies and distributors/aggregators Support broader strategic content partnerships with streaming platforms, broadcasters, and other IP owners, working closely with the US-based Content Acquisitions & Partnerships team Play a key role in shaping the Tubi Canada content strategy, ensuring the offering resonates with Canadian audiences and drives viewing growth Manage ongoing relationships with creators and partners, including onboarding, marketing collaborations, & partnership growth Track and analyze partner performance to identify growth and optimization opportunities Your Background: Demonstrated knowledge of the Canadian content and streaming landscape, with established relationships across the creator ecosystem 7+ years of experience in the creator economy, digital media, streaming, or content partnerships Track record in creator acquisition and/or partner management Strong empathy and understanding for creators and a keen understanding of their needs, challenges, and business models Exceptional communication and relationship-building skills, with a demonstrable ability to work cross functionally Strong da

About the Role: Tubi is seeking a highly skilled and experienced Senior QA Automation Engineer to lead quality assurance initiatives for our cutting-edge streaming and AI-driven product features. This pivotal role involves ensuring exceptional end-to-end user experiences, robust streaming playback, and the accuracy and integrity of our AI/ML features across web, mobile, and OTT platforms. We're looking for a candidate with a strong background in streaming QA and deep technical knowledge of media workflows. You'll be instrumental in collaborating with engineering, product, and data science teams to define comprehensive QA strategies that guarantee both functional excellence and data-level quality. This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office three days/week. What You'll Do: Design and lead test strategies for streaming workflows, playback systems, and AI-powered features. Test across platforms (web, mobile, and connected TV) to ensure functional parity and playback stability. Validate streaming performance—including ABR logic, encoding pipelines, and DRM integrations—under diverse real-world conditions. Debug with precision using tools like Charles Proxy, Chrome DevTools, ADB, and Xcode. Collaborate with data and ML teams to validate AI model updates, recommendations, and personalization accuracy. Leverage AI-assisted QA tools to enhance regression coverage, UI validation, and anomaly detection. Contribute to automation and CI/CD frameworks, driving faster, more reliable releases. Help drive a shift-left testing approach by engaging early in the software development lifecycle, partnering with product managers, engineers, and data scientists to identify quality risks, define test strategies, and ensure testability during requirements and design phases. Oversee QA deliverables for multiple concurrent releases and ensure seamless sign-off for production launches. Monitor live environments for playback or reco

About the Role The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding, and ads optimization that shape the future of streaming. We are seeking a VP / Director of Machine Learning Engineering to lead and build a high-performing team while staying close to the technical work. This is a hands-on leadership role: you will set the strategic direction for our recommendation, personalization, and ads optimization systems, including recommendation foundation modeling, and you will stay in the algorithms and the code, conducting deep dives into modeling components and guiding the hardest technical decisions yourself. You will tackle complex machine learning problems at scale and partner closely with cross-functional teams to ship solutions that measurably improve how hundreds of millions of viewers experience Tubi. What You’ll Do Lead, build, and grow a high-performing ML engineering team, fostering a culture of technical excellence, ownership, and rapid iteration. Define and drive the ML strategy and long-term technical roadmap for recommendation, personalization, and ads optimization, including recommendation foundation modeling, identifying opportunities for ML to shape Tubi’s broader product and business strategy. Stay hands-on: conduct deep dives into algorithmic components and systems, ensuring models are optimized for both performance and scalability across regions and product areas. Lead the design, development, and implementation of advanced recommendation systems and algorithms, contributing directly to the most challenging technical problems. Build and deploy robust, full-stack ML pipelines: data extraction, feature development, model training, testing, deployment, and serving. Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring

About the Role: Tubi is one of the largest free streaming platforms in the US, serving a large-scale streaming audience across Web, iOS, Android, Roku, Fire TV, Apple TV, and game consoles. Quality at this scale isn't a checkbox — it's a competitive advantage. We're looking for an Automation Engineering Manager to lead the team responsible for building and operating Tubi's multi-platform test automation infrastructure. You will own the strategy, tooling, and execution quality across our client surfaces — from video playback and ad delivery to content discovery and onboarding. This role is for a hands-on technical leader who can set direction, influence cross-functional roadmaps, and stay close enough to the code to guide architecture, review critical implementation decisions, and unblock complex technical issues. You will build a team that ships reliable automation at speed — and you will help the team move toward AI-native automation practices: fluent in AI tooling, proactive about applying it, and disciplined about using it responsibly. This is a hybrid role based out of either our San Francisco or Toronto office. You must be willing to travel to either location at least 2 days a week. What You'll Do: Test Strategy & Quality Planning Define and own Tubi's multi-platform automation strategy — covering Web, iOS, Android, CTV (Roku, Fire TV, Apple TV, Smart TVs, game consoles), and API layers. Establish testing standards, coverage targets, and quality gate policies across the CI/CD pipeline to protect release confidence and production reliability. Design specialized test strategies for business-critical scenarios: video playback (HLS/DASH), ad insertion, content recommendation surfaces, and user authentication flows. Use AI-assisted analysis (e.g., failure pattern clustering, test gap detection) to continuously improve test strategy based on real production signal and defect trends — not gut instinct. Automation Framework & Infrastructure Lead the

About the Role: Site Reliability Engineering (SRE) at Tubi is not a traditional operations team. We are a software engineering organization that applies a developer's mindset and toolkit to the challenges of building and running large-scale, distributed systems. Our mission is to engineer resilience from the ground up, enabling our product teams to innovate rapidly while ensuring our users have a stellar experience. We own the availability, latency, performance, and capacity of our platform, and we achieve our goals through a culture of data-driven decision-making, blameless learning, and relentless automation. As a Senior Site Reliability Engineer, you are a hands-on engineer who blends deep software development expertise with a passion for operational excellence. You will be responsible for designing, building, and running the resilient, scalable, and increasingly self-healing systems that power our products. You will apply sound engineering principles to solve our most complex reliability challenges, with a mandate to automate everything, eliminate toil, and write robust, maintainable code. You will be a force multiplier, mentoring other engineers and elevating the site reliability bar for the entire organization. This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week. What You'll Do: System Architecture & Design: Design, build, and maintain scalable, highly available, and fault-tolerant distributed systems. Partner with development teams as a reliability consultant, reviewing designs and influencing architectural decisions to ensure new services are built with reliability, observability, and performance as core principles, not afterthoughts. Automation & Software Development: Write robust, performant, and maintainable code to automate operational tasks, and CI/CD pipelines. Build the internal tools, libraries, and frameworks that enable engineering teams to self-service their

About the Role: The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding, and ads optimization that shape the future of streaming. We are seeking a Director of Machine Learning Engineering and Infrastructure to lead a hybrid team bridging advanced ML engineering with world-class infrastructure design. In this role, you will own the strategic direction and execution for scaling our machine learning capabilities while ensuring our distributed systems and infrastructure can support innovation at massive scale. You will combine technical depth with leadership excellence to guide teams that deliver both foundational ML systems and high-performance distributed services. This is a hybrid role for our Toronto office. What You'll Do: Lead and manage high-performing teams across ML engineering and ML infrastructure, fostering a culture of innovation, collaboration, and growth. Define and execute the strategic roadmap for ML systems, including recommendation, personalization, and ads optimization. Oversee the design, development, and deployment of scalable ML pipelines: data ingestion, feature engineering, model training, evaluation, and serving. Architect distributed systems to support ML workloads at scale, ensuring reliability, observability, and operational excellence. Partner closely with Product, Engineering, and Content teams to align on business goals and deliver impactful ML-driven experiences. Support best practices in experimentation, evaluation, and ML system monitoring. Ensure cost efficiency, scalability, and performance in ML infrastructure investments. Your Background: 10+ years of industry experience spanning machine learning engineering and distributed systems. 3+ years of leadership and management experience, with a proven ability to build and lead strong t

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We are seeking a hands-on Data Center Technician, IT Contractor to support the installation, deployment, relocation, cabling, inventory, maintenance, and decommissioning of servers, network equipment, storage systems, and other IT infrastructure. The successful candidate will follow established procedures, maintain accurate documentation, and coordinate effectively with internal technical teams and data center personnel. This role will be a 6-month contract fully on-site, based out of the downtown Toronto, ON Beanfield data center, with travel to Tenstorrent office locations and other data center facilities as required. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are You bring approximately 2 to 5 years of hands-on experience in data center operations, IT infrastructure, server or network hardware, or a similar technical role. You are comfortable working with servers, network equipment, storage systems, racks, rack layouts, and copper and fiber optic cabling. You are detail-oriented, organized, and able to follow documented procedures, cabling standards, installation instructions, and safety requirements. You communicate clearly, work well wi