Ai Knowledge Analyst in Toronto

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team, applying frontier technologies to the world's biggest financial problems. We're looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn't a place for complacency, it's where ambitious people do the best work of their careers. We're a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. The Software Platform team accelerates developer velocity and increases system reliability by building the foundational platforms and tools that power Robinhood engineering. Within this group, the Kubernetes Compute team focuses on building and operating a highly available, scalable Kubernetes-powered container platform. We ensure that our infrastructure seamlessly supports reliable application deployments, integrates core platform capabilities, and enables multi-region scalability. We are expanding our core container systems to support our next phase of technical growth! As a Software Developer, you will focus on building, maintaining, and scaling our container provisioning platforms. Working alongside senior engineers, you will write code to improve our infrastructure capabilities and actively participate in our technical transition to Amazon EKS. In this role, you will collaborate with teams across the organization to ensure robust platform integrations for everyday application needs like security and networking. Your efforts will directly improve system visibility, automation, and reliability across the platform. This role is based in our Toronto office(s), with in-perso

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. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically eva

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. Machine Learning is at the heart of Lyft’s products and decision-making. Machine Learning Engineers at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges, from pricing and marketplace frameworks that ensure reliability and competitiveness, to agentic AI platforms that automate analytical workflows, to behavioral detection systems that protect the integrity of our network. We operate at the intersection of applied ML and real business impact, shipping models that directly influence revenue, rider experience, and partner trust. Lyft Business builds products that help organizations move the people who matter most—employees, customers, patients, and guests—easily and efficiently. Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools. These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs. We're looking for a Machine Learning Engineer to design, build, and deploy ML systems across Lyft Business. This is a high-scope role: you won't be siloed into one problem area. Instead, you'll move across pricing algorithms, fraud and behavior detection, agentic AI systems, and emerging ML applications as the business evolves. You'll write production-quality code, own models end-to-end from prototyping through deployment, and collaborate closely with Data Scientists, Product Managers, and Software Engineers to translate complex business problems into scalable ML solutions. This role is ideal for someone who is technically versatile, energized by variety, and wants to see th

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. As the Engineering Manager for the Lakehouse Foundation team, you will lead a group of engineers responsible for the foundational data layer that all of Lyft's data systems and emerging AI workloads are built on. The team owns catalog and metadata management, table formats and storage, and the access patterns and gateways through which other engineering teams interact with Lyft's data. As Lyft converges on a unified lakehouse architecture, this team builds and operates the single source of truth that powers analytics, machine learning, experimentation, and every business decision made from data. You will play a key role in shaping the team's technical direction, partnering with peer Data Platform teams on a multi-year platform evolution, and developing engineers who operate with autonomy on systems of significant scale and complexity. Lyft's Infrastructure teams build the foundational systems that the rest of engineering depends on to move fast, ship reliably, and scale efficiently. These are high-leverage roles where the work you and your team do has a multiplicative effect across the company. We're looking for experienced leaders who can balance the discipline of operating critical infrastructure with the curiosity to keep evolving how Lyft builds. Engineering at Lyft is a place where managers and engineers operate with high ownership and strong technical judgment. Our engineers expect their managers to be honest, available, and focused on the work that matters: developing their teams, removing obstacles, and giving people the support they need to do their best work. We build teams that are inclusive, technically rigorous, and have a strong sense of ownership for what they build. Responsibilities: Lead a team responsible for Lyft's foundational data layer, including catalog and metadata management,

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 Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers. We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection. As a Data Scientist working on Causal Inference in SCC, you'll partner with a strong team of engineers, product managers, designers, and operations leaders to deliver a personalized and exceptional experience for Lyft customers, using rigorous causal inference to guide the highest-stakes decisions we make. We're looking for a motivated and talented Data Scientist with deep causal inference expertise to join the SCC Data Science team. You'll partner closely with the area's tech lead on high-impact work spanning AI-powered support products, differentiated service, and operations optimization. The ideal candidate brings sharp applied inference intuition, a bias toward impact, and the ability to cut through ambiguity in complex problem spaces. You'll work on projects like: Design rigorous experiments and quasi-experiments to measure the causal impact of SCC product and AI-agent launches, and drive data-informed launch decisions. Build causal ML models to optimize concession budget allocation, targeting the right support credit, to the right rider or driver, at the right moment to maximize trust and business impact. Quantify the long-term effects of support-experience changes on rider and driver retention, and uncover heterogeneous treatment effects across our community. Deliver strategic insights on quality–cost tradeoffs, empowering leadership to balance service quality, coverage,

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 Senior Analyst to join our Business Forecast & Planning team within Customer Care Operations. This role sits at the center of forecasting and capacity strategy for our global support organization, translating complex operational and business signals into clear, actionable plans. You'll partner closely with operations leadership to keep resourcing aligned with the business, separating what truly matters from the noise, and helping shape decisions that affect how we staff and scale support. Responsibilities: Support the development and upkeep of the models and frameworks that connect business drivers to staffing and resourcing decisions Translate large, complex, and sometimes ambiguous data into clear, actionable insights that support leadership recommendations Own day-to-day planning execution, from dashboards maintenance and reporting to business reviews, with a sharp focus on accuracy and the details that matter Leverage AI tools to build and maintain dashboards, reports, and analyses that support the team's recommendations and insights Identify and help drive opportunities to improve how the team plans and operates Move quickly on ambiguous, time-sensitive requests, using modern tools to work smarter and faster Experience: 2+ years in planning, forecasting, capacity/resource management, or a related analytical role; consulting, investment banking, FP&A, or ops strategy backgrounds also fit well Sharp analytical mindset with hands-on SQL and Python skills AI fluency, comfortable using AI tools to accelerate analysis and problem-solving Strong business acumen paired with genuine curiosity about how large, complex business systems work; fast learner with a bias towards action, comfortable building context quickly across new systems and stakeholders Self-directed, with a track

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 Urban Solutions (LUS) is North America’s leader in micromobility. We own, operate, or provide hardware and software solutions for bikeshare and scootershare programs in 50+ global markets including Montreal, Toronto, London, New York City, Mexico City and others. Our rapidly growing active fleet includes state-of-the-art charging stations, electric bikes, and scooters, and services hundreds of millions of rides per year. Data and analytics are at the heart of Lyft's products and decision-making. You will play a key role in shaping the future of bikeshare by leveraging data to improve the performance of our bikeshare and scooter markets. A successful candidate thrives in a dynamic and collaborative environment, has a natural curiosity, and isn’t afraid to dive deep. In this role, you will collaborate closely with Operations, Policy, Engineering, Product and Finance teams to drive data-informed strategies that align our operations and products with city transportation goals and user needs. You will work in a fast-paced environment where analytical insights directly impact decisions ranging from pricing and product features to long-term investments in bikesharing infrastructure. We’re looking for a passionate and driven Data Analyst to tackle some of the most complex and impactful challenges in micromobility. If you’re excited about shaping the future of urban mobility through data, we’d love to hear from you. Responsibilities: Partner with Product, Engineering, Policy, Operations, Finance and other cross-functional stakeholders on initiatives to conduct deep-dive analyses to root cause issues and propose solutions Develop frameworks, business logic and scalable processes to streamline reporting and drive decision-making Forecast operational requirements and investments needed to

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. Data and analytics are at the heart of Lyft Business's products and decision-making. We're looking to hire a Data Analyst to support our Self-Serve segment — the fastest-growing part of Lyft's B2B portfolio, serving small and mid-size businesses across North America. This is a hands-on role for an analyst who is energized by turning product and customer data into insights that shape strategy — and who builds those insights on a foundation others can trust and reuse. You will be the dedicated analytical partner to the Self-Serve product team, measuring how new features — a redesigned signup experience, onboarding improvements, and lifecycle campaigns — drive customer activation and growth. You'll own the funnel from acquisition through engagement, define the metrics that matter, and deliver the insights that inform where the business invests next. The ideal candidate pairs analytical rigor with a builder's instinct — turning recurring questions into well-defined, reusable datasets instead of one-off answers — and can translate findings into a clear narrative for both technical and non-technical audiences. Responsibilities: Produce high-impact analyses on Self-Serve performance that directly inform product and go-to-market strategy Own the Self-Serve funnel — acquisition, signup, onboarding, and engagement — building the dashboards and datasets that give the team real-time visibility into product health Define what the team's core metrics mean and where they live, so every dashboard, report, and tool returns the same answer to the same question Partner closely with Product and Engineering to validate instrumentation and surface data gaps before they distort the funnel or new features launch — catching the data quality issues that stay invisible until someone goes looking Turn recurring reporting into w

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 vision of the Safety & Customer Care (SCC) team is to foster long-term loyalty to Lyft with every support interaction. If we are successful, a Lyft customer will rarely interact with Lyft Support. But when that interaction occurs, their issue is resolved quickly, effectively, and with true care. For a Lyft customer, their experience of Support should be that “Lyft cares about me and made the experience easy.” As a Data Analytics Lead, you’ll partner directly with cross-functional stakeholders to identify opportunities and design solutions for improving our customers’ support experience. You’ll leverage your analytical expertise to deliver actionable insights and recommendations to drive quality business decisions with customer-facing impact. The ideal candidate is a critical thinker and exceptional problem solver who can build strong relationships with different teams, and who is eager to serve as a leader within the broader Support organization to drive our business forward. Responsibilities Partner with Product, Engineering, Data Science & Analytics, Business Operations and other cross-functional stakeholders to achieve business goals Develop frameworks and scalable processes to drive decision-making and prioritization Define the metrics used to measure the success of strategic initiatives and health of our support platform; build dashboards to track metrics over time Design A/B tests and execute analyses to evaluate the impact of new product features and operational improvements Work closely with cross-functional partners to deliver data-driven insights and actionable recommendations for continuously improving the customer support experience Monitor and diagnose KPI performance and present findings to senior leadership Experience Degree in a quantitative field like statisti

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team Stripe processes over $1T in payments volume per year, which is roughly 1% of the world’s GDP. The tremendous amount of data makes Stripe one of the best places to do machine learning. The ML Infra team builds services and tools that power every step in the ML lifecycle, including data exploration, feature generation, experimentation, training, deploying, serving ML models, and building LLM applications. With the phenomenal developments happening in the field of AI, we are positioned to accelerate the adoption of AI/ML across all parts of the company by building highly scalable and reliable foundational infrastructure. What you’ll do You will work closely with machine learning engineers, data scientists, and product engineering teams to enable seamless end-to-end experience in building solutions across data, analytics, and AI/ML platforms. You will build the next generation of ML Infra services and major new capabilities that substantially improve ML development velocity and MLOps maturity across the company. Responsibilities Designing and building scalable, reliable, and secure services for notebooks, ML model training, experimentation, serving, and LLM applications across multiple regions. Creating services and libraries that enable ML engineers at Stripe to seamlessly transition from experimentation to production across Stripe’s systems. Working directly with product teams and ML engineers to improve their day-to-day pr

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: 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