Design Technologist in Toronto

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Driver team is dedicated to fostering a platform of high-quality service by empowering drivers to perform their best. We are looking for a product-minded engineer who wants to build and improve products that sit at the center of the core driver experience. Products you drive will solve pain points that matter most to drivers by streamlining key interactions, reducing friction, and creating systems that feel intuitive, fair, and supportive. As an engineer at Lyft, you'll collaborate with teams like product, data science, analytics, and operations on code that empower us to iterate quickly, while focusing on delighting our passengers and drivers. Responsibilities: Design and implement backend features end-to-end with clear ownership, delivering well-scoped work from technical design through to production with moderate guidance from senior engineers Write clean, reliable, well-tested code that meets team standards and holds up in code review Participate actively in code reviews, giving specific and constructive feedback while continuing to develop your own review instincts Debug and resolve issues across backend services including performance bottlenecks, reliability problems, and data integrity issues Collaborate with product managers, designers, and partner engineering teams to clarify requirements and surface technical constraints early Contribute to technical discussions and help evaluate implementation approaches for new features Write unit and integration tests for your own code and develop familiarity with the team's broader testing and observability practices Address technical debt and make incremental improvements to existing services as part of regular development work Participate in on-call rotations, respond to production incidents, and support teammates in mitigating custome

About the Team: Tubi's Internal Tools team is at the forefront of AI integration, developing everything from developer resources to production-grade AI for business operations. We are the group responsible for turning AI from an experiment into an operating capability: training, infrastructure, developer agents, and AI-powered business systems. Engineers operate with high ownership and autonomy, collaborating on shared architectural decisions and AI infrastructure. What You'll Do: Own systems end to end — design them, build them, and support them in production. Lead the projects you own: sequence the work, decide what lands first, and set technical direction for the engineers working with you. Sit with the people who use what you build, and turn what you learn there into a system. Design the service boundaries, contracts and schema evolution that let our platforms grow without breaking the teams depending on them. Make our AI systems dependable in production: evaluation harnesses, human approval steps before an agent acts, retries that handle a model returning something unexpected, and cost tracking that tells you what a task costs before you run it. Build what other engineers build on — agent skills, tool and MCP integrations, shared libraries — and raise the bar through code review, design discussion and mentoring. Spot the platform work nobody has asked for yet, make the case for it, and build it. Your Background: 5+ years of professional experience building and operating production systems, from design through production ownership. A system you designed and can walk us through end to end — where its boundaries sit, what constrained it, and what you chose against. Strong programming proficiency in a statically typed language such as Rust, Go, C++, Java, Kotlin, C#, or TypeScript. Production Rust is a plus rather than a requirement. You have owned a service in production: you wrote the runbooks, you knew what it cost, and you were the one paged when it broke. Expe

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Role Overview As the Okta Research & Design (ORD) Jira Owner & Administrator , nested within the Technical Program Management (TPM) organization, you will define and execute the strategy for how ORD plans, tracks, and reports on engineering work within the full toolchain of Atlassian Jira, Jira Advanced Roadmaps (Plans), Confluence, Rovo, and AI integrations. In this role, you act as a critical bridge between product & technical leadership, agile teams, and cross-functional business units — translating methodology, best practices, and process frameworks into practical workflow improvements that accelerate delivery and reduce manual overhead for a 1,000+ person engineering, product, and design organization. By optimizing tooling configurations, automating reporting, and eliminating fragmented management processes, you will directly accelerate ORD’s developer velocity and strengthen operational efficiency. Core Responsibilities 1. Platform Ownership & Strategic Tooling Direction Strategic Vision: Define, implement, govern an AI-led strategy for utilizing Jira for product planning, tracking, and reporting tooling that supports end-to-end portfolio tracking from high-level corporate objectives down to sprint-level stories. E2E Ecosystem Management: Complete ORD ownership of the toolchain (Jira, Jira advanced Roadmaps, AI integrations, Confluence), overseeing architecture, schema updates, workflow management, screen/notification schemes, cu

About the Role: We're hiring Senior and Staff Data Platform Engineers to join the Data Infrastructure teams in Toronto. Together these teams own the infrastructure that processes billions of events per day: Spark-on-Kubernetes, Flink and Kinesis pipelines, a multi-petabyte Delta Lake, a large-scale MemoryDB feature store, Databricks multi-environment operations, and the catalog and lifecycle systems that govern it. The team is small and senior. Each engineer owns major platform components: you design it, build it, and support it in production. 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: Spark-on-Kubernetes — EKS-based compute platform for Spark workloads: cluster configuration, Pod Identity IAM, job environment setup, Kustomize overlays, and shadow canary validation Event ingestion — Rust services and Flink jobs processing billions of events per day over Kinesis; throughput, reliability, on-call response, and AI-assisted operational tooling to reduce toil Platform infrastructure — Terraform modules for environment provisioning, cross-account AWS IAM, ARC runner infrastructure, and CI/CD for data platform changes Feature store and ML compute — Flink-based real-time feature pipelines feeding a large-scale MemoryDB cluster; GPU capacity governance and Databricks multi-environment operations for ML training workloads Workflow orchestration and CDC — Airflow-based DAG deployment, change data capture pipeline operations, and data quality monitoring Your Background: 3+ years building and operating production data platform infrastructure at the cluster or platform level, across Spark, Flink, Kinesis, Kubernetes, or equivalent Deep experience in at least one of: Spark-on-K8s cluster operations, Rust-based data or systems engineering, Kubernetes platform engineering and IaC, or data catalog and governance tooling Production AWS experience or equivalent: EKS, S3, Kinesis, and mu

About the Role: The Growth 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 full funnel user acquisition and growth, including SEO user registration, onboarding, and account management. As a Staff Engineer (L5) on this team, you act as the technical leader for one or more Growth areas. You own the technical architecture and direction, solve ambiguous problems that few others can, and influence cross-functional teams across multiple pods. You will work closely with Product and Design to develop cutting-edge, experiment-driven features, while driving the front-end architecture that ensures performance and scalability for millions of users. 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: Own the technical roadmap and architecture for a Growth area with large amounts of ambiguity: driving direction across web, mobile web, and smart TV platforms, and influencing the team to invest in new projects. Solve challenging, ambiguous problems with a focus on scalability and performance; proactively identify systemic issues and propose innovative solutions. Lead and drive innovation in building experiment-driven features; independently design, implement, and interpret a series of A/B experiments that move growth metrics. Lead and coordinate major rollouts and releases: including cross-team coordination, migrations, and phased releases of major initiatives across Web and OTT apps. Establish team-wide quality and engineering standards; set the bar for code quality and front-end best practices. Identify and implement improvements in shared UI components, platform-specific optimizations, and overall fr

About the Role: We are looking for a talented Automation Engineer to join our Automation Engineering team in Toronto. In this role, you will be responsible for designing and implementing automated tests for Mobile development. You will collaborate closely with QA engineers and developers to build scalable test frameworks, improve automation coverage, and contribute to the efficiency of our multi-platform release process. You will also design data-driven end-to-end checks around playback and ad insertion , integrate them into CI/CD pipelines as quality gates, and operate a reliable device lab to prevent regressions from shipping. Your work will directly accelerate testing and release velocity while improving revenue-critical reliability across Tubi’s Android and IOS apps. 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, implement, and maintain automated tests for mobile development (Android & iOS) Contribute to the development and optimization of cross-platform automation frameworks. Write and maintain test scripts in JavaScript/TypeScript , using frameworks such as Puppeteer, Appium, WebDriverIO, Selenium. Ensure test cases are integrated into CI/CD pipelines and provide reliable feedback on product quality. Help identify flaky tests, investigate root causes, and improve test stability. Collaborate with developers and QA engineers to clarify requirements and improve test strategies. Participate in code reviews and follow best practices for test automation . Your Background: Bachelor’s degree or above in a technical field (e.g., Computer Science, Engineering, Mathematics), or equivalent industry experience. 3+ years of hands-on experience in automation testing for mobile devices Strong programming skills in JavaScript/TypeScript (preferred), or Python/Java. Experience with automation frameworks (e.g. Puppeteer, Appium,, WebDriverIO, Selenium, Playwright, T

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 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

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! The Role As a Senior Solutions Engineer, you will play a critical role at the intersection of data, technology, and customer impact. You will lead the design and delivery of scalable, reliable, and high-impact technical implementations for our enterprise clients. Working with diverse and complex datasets across industries, you’ll build and optimize end-to-end analytics solutions that directly influence how customers engage with the Forma platform. You’ll partner cross-functionally to identify opportunities, scope high-value solutions, and deliver outcomes that drive measurable business impact. This is a highly visible, client-facing role that combines hands-on technical expertise with strategic thinking. What You’ll Do Lead strategic technical engagements with enterprise clients, guiding solution design for complex business challenges using the Forma platform Design, build, and optimize scalable data architectures, pipelines, and workflows (e.g., PySpark, Databricks) Translate business requirements into robust, production-ready data solutions Design and deliver custom code and customer-specific integrations to extend the Forma platform for unique client requirements Partner with Professional Services to extract, transform, and analyze client data to optimize incentive compensation and sales performance strategies Collaborate with Product, Engineering, and Customer Success to deliver high-quality, actionable datasets and insights Drive improvements in data infrastructure, perfor

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit’s Ads Data Science team is looking for a highly experienced Staff Data Scientist to advance the intelligence powering the advertiser experience on Reddit. In this role, you'll take deep ownership of a high-impact problem space within advertising, specializing in measurement, identity, and signal quality. This is a high-impact, high-autonomy role where you'll influence strategic direction, set a high technical bar, and drive cross-functional initiatives across one or more critical focus areas in the Ads organization. Responsibilities: Design the Future of Ads Identity: Develop/employ probabilistic models for identity resolution. Design the methodology that links on-platform and off-platform actions to maximize addressability while honoring privacy. Advance Lift Methodologies & Experimentation: Own the statistical rigor behind Reddit’s Brand and Conversion Lift products. Innovate experimental design and develop infrastructure that supports large-scale, high-velocity, low-bias testing for advertisers. Maximize Signal for Predictive Performance: Define the strategy for new signal sources. You will mathematically quantify the value of these signals and work with modeling teams to incorporate them into predictive models, directly improving bidding efficiency and ROAS. Define Ground Truth & Evaluation Frameworks: Solve the industry-wide challenge of validating identity and measurement. Design the objective functions and truth sets used to train our models and measure the incremental impact of our identity graph.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft is seeking a qualitative User Experience Research Intern to join our team, which aspires to elevate the user experience for our drivers and riders across 300+ cities nationwide. You will conduct research studies, as well as participate in studies alongside more senior researchers from which you’ll gain strong mentorship. You will partner with Design, Product Management, Analytics, and Engineering in order to derive deep insights about our users’ behaviors and attitudes, and communicate results and actionable recommendations across the company. Interns contribute to user-facing products, working side-by-side with top User Experience Research team members in the industry while having autonomy from the get-go. Lyft fosters a collaborative environment in the office, so there's always a sharp mind eager to hear about your next idea. So what's yours? Responsibilities: Design and conduct studies across key Lyft product areas -- independently and in conjunction with more senior researchers. You will utilize methods such as ethnographic & field research, diary studies, surveys, user/usability testing (remote and in-person), guerrilla research, and any other methods you find impactful Review, analyze, and communicate qualitative and/or quantitative data to generate tactical and strategic insights, as well as actionable recommendations which drive product innovation and design improvements for users Experience: Currently pursuing a Master's or PhD degree in Human-Computer Interaction, Anthropology, Design, Psychology, Cognitive Science, or a related field from a university in Canada with a graduation date between December 2027 and Summer 2028 (required) Available during Summer 2027 for an internship in Toronto Extraordinary organizational skills and meticulous eye for detail Str