Eng in Canada

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: 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

**English version below** Doit être local à Montréal Vous souhaitez travailler dans le domaine de la technologie au sein d'une banque d'investissement? Nous recherchons une personne pour rejoindre une équipe dynamique en tant qu’ Ingénieure Fiabilité de Site (Site Reliability Engineer) pour l’un de nos clients. Le Site Reliability Engineering (SRE) est une discipline orientée production, axée sur l’amélioration de la disponibilité des services systèmes, de l’observabilité, de l’évolutivité, de la performance et de la fiabilité des produits technologiques, en appliquant de solides principes d’ingénierie logicielle et en adoptant les technologies et outils les plus récents. Nous serions ravis de vous rencontrer si vous : Vous intéressez aux systèmes distribués et au travail sur des services hautement évolutifs, fiables et à grande échelle. Aimez évoluer dans un environnement dynamique et n’avez pas peur de changer les choses pour les améliorer. Appréciez les nouveaux défis technologiques et la résolution de problèmes complexes. Croyez qu’une équipe qui collabore efficacement est véritablement plus intelligente que la personne la plus brillante qui la compose. Aspirez à évoluer en tant que personne, coéquipier·e et ingénieur·e. Faites preuve de détermination, de motivation et d’un profond sens des responsabilités. À propos de mtrois : Depuis 2010, mtrois aide ses clients à résoudre leurs défis commerciaux et technologiques. Nous sommes une société de conseil en technologie et en affaires avec une main-d'œuvre mondiale qui réalise des projets commerciaux et informatiques significatifs dans certaines des plus grandes organisations de services financiers du monde. Services principaux Consulting et Conseil Services gérés Programme de diplômés Alumni Programme Alumni Pro Nous avons une présence mondiale et sommes experts dans la fourniture d'une qualité exceptionnelle à notre base de clients, offrant des services de conseil dans les domaines du risque, de la réglementa

**English version below** Doit être local à Montréal Vous souhaitez travailler dans le domaine de la technologie au sein d'une banque d'investissement? Nous recherchons une personne pour rejoindre une équipe dynamique en tant qu’ Ingénieur(e) Data pour l’un de nos clients. Ce poste est destiné à un rôle d’ingénierie des données au sein de l’équipe MongoDB et Kafka . Nous sommes un groupe hautement technique qui réalise simultanément divers projets pour plusieurs secteurs d’activité. Les responsables métier et les experts sont répartis à l’échelle mondiale, ce qui rend de solides compétences en communication essentielles pour ce poste. Le ou la candidat(e) travaillera en étroite collaboration avec nos partenaires informatiques afin d’analyser les besoins métier et de mettre en œuvre les solutions répondant à ces exigences. À propos de mtrois : Depuis 2010, mtrois aide ses clients à résoudre leurs défis commerciaux et technologiques. Nous sommes une société de conseil en technologie et en affaires avec une main-d'œuvre mondiale qui réalise des projets commerciaux et informatiques significatifs dans certaines des plus grandes organisations de services financiers du monde. Services principaux Consulting et Conseil Services gérés Programme de diplômés Alumni Programme Alumni Pro Nous avons une présence mondiale et sommes experts dans la fourniture d'une qualité exceptionnelle à notre base de clients, offrant des services de conseil dans les domaines du risque, de la réglementation et de la conformité ; Produits des fournisseurs ; Support d'application ; Développement d'application ; Cyber et sécurité de l'information ; Science des données et DevOps. Notre programme Expert offre aux professionnels expérimentés l'accès à des rôles de premier plan dans la technologie, la finance, l'aviation et l'assurance. Rejoignez-nous pour travailler sur des projets technologiques révolutionnaires, des plateformes de trading internationales aux applications critiques pou

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! About the Team We build enterprise software that helps organizations optimize sales performance and improve go-to-market agility. Our engineering organization includes multiple product application teams responsible for delivering core customer-facing capabilities. We are seeking Senior Backend Engineers to join our application teams. You’ll work alongside staff, senior, and early-career engineers to design, build, and scale backend systems that power enterprise-grade product workflows. This is an opportunity to work on complex product and data problems while contributing meaningfully to technical decisions, system quality, and team delivery. We are low on meetings and high on accountability. Most of the team is in the EST time zone, with a few located in AST, PST, and Central as well. What you’ll be doing You will play an important role in the continued evolution of our application stack. You will design and build backend capabilities for complex product workflows, contribute to system design discussions, and help ensure our systems remain maintainable, reliable, and scalable as we grow. As a Senior Backend Engineer, you are expected to operate with strong ownership and sound technical judgment. This includes identifying risks in the work you own, surfacing edge cases, asking thoughtful questions, and proposing improvements that strengthen the quality and reliability of the system. You will: Design and build backend services that power complex product workflows. Contribute to d

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! About the team Engineers on this team build the application our customers and internal teams use to configure, operate, manage, and visualize complex incentive compensation workflows. There are many complex and difficult areas across the product, especially across frontend architecture and user experience, because of high data volumes, wide configurability, complex business logic, and mission-critical operational workflows. The work is not just about building screens; it is about helping users understand, act on, and trust complex compensation data and operational processes. We are low on meetings and high on accountability. Most of the team is in the EST timezone, with some teammates in PST and Central. We are far from maintenance or simple progressive evolution in many areas; there is a lot of room to make a meaningful impact on the overall user experience, product architecture, and frontend design patterns. What you’ll be doing Reporting to the VP of Engineering, the Staff Frontend Engineer will play a critical role in shaping the technical direction, architecture, and long-term evolution of Forma’s customer-facing and internal operations experiences. You’ll operate as a frontend technical leader, working across teams to drive alignment, set standards, and solve complex, ambiguous problems in a highly configurable, data-intensive product. You’ll partner closely with product, design, engineering, and leadership to define not just what we build, but how we build it — ensuring

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! The Opportunity As a Staff Security Engineer, you will be a hands-on technical leader strengthening security across Forma's application, cloud infrastructure, development lifecycle, internal systems, and incident-response practices. Security today is shared across Engineering and DevOps. You'll work closely with both teams and have real room to shape how Forma approaches security as we grow. Depending on your interests and the needs of the business, the role could develop into a deeper individual-contributor position or help build a dedicated security team. You'll work directly with Engineering, DevOps, IT, Product, Legal, and Privacy to identify risks, design practical controls, automate security processes, and help teams ship secure and reliable software. What you'll do Cloud and infrastructure security Design and implement security controls across Forma's AWS environments, with a focus on IAM, least-privilege access, service identities, and account boundaries. Embed security requirements into Terraform and other Infrastructure as Code, and improve secrets, certificate, encryption-key, and credential management. Build automated checks for insecure configurations, excessive permissions, exposed resources, and configuration drift across Kubernetes, containers, serverless workloads, networking, and data services. Application, data, and AI security Run threat modelling and security architecture reviews for new products, services, APIs, data pipelines, and third-party integrations