Technical Community Manager 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. Lyft is looking for an IT Systems Engineer to lead the technical side of integrating newly acquired companies into Lyft's IT environment. You'll be responsible for migrating collaboration tools, SaaS platforms, and identity systems from acquired teams into Lyft's stack, with minimal disruption to either side. We're looking for a self-starter who's equally comfortable driving projects independently and partnering with others to get things done. The ideal candidate brings strong attention to detail, creative problem-solving, and a genuine drive to automate processes and improve efficiency across the IT organization. Responsibilities: Manage SaaS integration and consolidation during merger and acquisition activity, ensuring smooth platform migrations, data integrity, and minimal disruption across merged organizations Provide architectural, engineering, and operational support for corporate IT systems at Lyft Support single sign on integrations with Lyft’s primary identity provider, Okta. Leverage various APIs to write scripts and applications to automate IT Operations Support and work with IT, Security and other internal departments by building automation for repetitive tasks Write detailed and concise documentation and runbooks Engage with vendors to implement and improve services to best support Lyft’s needs Be a mentor to others in IT and act as a source for others Experience & Skills: 5+ years of experience managing corporate IT Systems Proven experience supporting IT integration during mergers, acquisitions, or divestitures, including SaaS platform consolidation and system migrations SaaS system application management including but not limited to: Gsuite, Okta, Atlassian, Slack Scripting experience leveraging GAM, Python, Bash, and/or equivalent tools Comfortable consuming RES

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. The divide between business needs and technical delivery is one of the most persistent challenges in enterprise technology, where People teams struggle to articulate requirements and engineering teams lack the business context to build truly impactful solutions. As a Senior Business Solution Architect for People at Lyft, you'll eliminate this gap by serving as the critical connection point between our People teams and our Corporate Engineering and IT (CEIT) organization. This customer obsessed role uniquely combines deep functional business expertise with strong technical acumen, with an AI native approach, enabling you to translate complex business needs into systemized, scalable solutions while driving AI-enabled transformation across the People function. We're seeking a strategic thinker who thrives at the intersection of business and technology, possesses exceptional communication skills across both technical and non-technical audiences, and is dedicated to architecting the future AI Native state of how the People function operates. You'll be the trusted advisor to both business leaders and engineering teams, ensuring our People organization has systems and processes that scale with our business while our engineering teams build solutions that truly move the needle. With AI fundamentally reshaping how the People function gets work done, your expertise will be critical in helping us responsibly harness these technologies to drive operational excellence. In this role, you'll reimagine People workflows through an AI-first lens, design business processes that balance operational excellence with technical feasibility, and champion automation that elevates teams from tactical execution to strategic impact. If you are a candidate who has the vision of what could be, who has the ability to cultivat

At Lyft, our purpose is to serve and connect, cultivating an inclusive environment where all team members can thrive. As the Business Systems Lead for Payroll & Time, you will lead Lyft's global migration onto Dayforce following recent acquisitions. Sitting within People Technology in Corporate Engineering and IT (CEIT), you'll join Lyft's Dayforce program at a formative moment: the initial rollout spans 12–15 countries over two-plus years, and you're joining early enough to directly shape how implementation, governance, and vendor management get done — not inherit a playbook someone else already wrote. You'll be backed by a mature, experienced Payroll Operations team who bring deep subject-matter expertise, while you own the technical and functional side: driving requirements, directing our systems integrator, and building the governance and vendor management model you'll run long-term as the platform's product/service owner. Sitting within People Technology in CEIT, you will drive requirements, make key functional decisions, and partner closely with Payroll Operations, HR, Legal, and Finance. You'll lead vendor delivery to ensure accurate, compliant payroll and time tracking across each migration wave, then own platform governance and vendor management long-term once the program stabilizes. We're looking for someone who can act as the translation layer between operations, executives, and technical teams — equally comfortable explaining payroll concepts to engineers and system constraints to business stakeholders. Responsibilities: Own Requirements and Direct the Implementation Partner Serve as the internal functional owner for the Dayforce payroll and time migration, driving requirements and directing the systems integrator partner. Translate payroll policy, collective bargaining terms, and statutory requirements — as defined by Payroll Operations and Legal — into actionable technical specifications. Validate vendor configurations against country-specific rule

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: 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: 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: 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: 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: 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

Want to work in technology at an investment bank? Graduate training, ongoing support, opportunities at leading global employers – the Alumni graduate program gives you everything you need. (And don’t worry, there’s no training bond. No exit fees, no hidden catches).Here at mthree, we pair great graduates with brilliant global businesses. Our clients include tier one investment banks and other organizations across a range of industries, from insurance to healthcare to travel.This is an exciting opportunity to join an FX Front Office support team in a major North American bank working on the Toronto Trading floor, supporting both front office users and a progressive eFX programme. What you'll do: Support IT solutions for various business lines globally including FX, Money Market, STIR and Options Offer technical expertise and support for the systems used Manage and resolving incidents and outages Manage requests for changes, system releases and capacity planning Disaster recovery, planning and execution How the Alumni program works: Apply via this job advert. Complete our assessment process. Get trained at mthree Academy in an online class for 4-8 weeks with other graduates. Join a mthree client for 12-24 months while receiving support and salary increases every 9 months. The vast majority then convert to permanent employees with the client at the end of the program. What you’ll learn at the mthree Academy: How to discuss production support activity at a high level including ITIL (information technology infrastructure library), monitoring, DevOps, SRE (site reliability engineering), and disaster recovery. How to discuss common financial topics, including financial markets, equity trading, derivatives, currency, treasury, regulation, and risk. How to write a basic computer program in Python, including user input, common data structures, and flow of control. How to use MySQL to perform CRUD (create, read, update and delete) operations on a relational database stored in

Want to work in technology at an investment bank? Graduate training, ongoing support, opportunities at leading global employers – the Alumni graduate program gives you everything you need. (And don’t worry, there’s no training bond. No exit fees, no hidden catches).Here at mthree, we pair great graduates with brilliant global businesses. Our clients include tier one investment banks and other organizations across a range of industries, from insurance to healthcare to travel.This is an exciting opportunity to join an FX Front Office support team in a major North American bank working on the Toronto Trading floor, supporting both front office users and a progressive eFX programme. What you'll do: Support IT solutions for various business lines globally including FX, Money Market, STIR and Options Offer technical expertise and support for the systems used Manage and resolving incidents and outages Manage requests for changes, system releases and capacity planning Disaster recovery, planning and execution How the Alumni program works: Apply via this job advert. Complete our assessment process. Get trained at mthree Academy in an online class for 4-8 weeks with other graduates. Join a mthree client for 12-24 months while receiving support and salary increases every 9 months. The vast majority then convert to permanent employees with the client at the end of the program. What you’ll learn at the mthree Academy: How to discuss production support activity at a high level including ITIL (information technology infrastructure library), monitoring, DevOps, SRE (site reliability engineering), and disaster recovery. How to discuss common financial topics, including financial markets, equity trading, derivatives, currency, treasury, regulation, and risk. How to write a basic computer program in Python, including user input, common data structures, and flow of control. How to use MySQL to perform CRUD (create, read, update and delete) operations on a relational database stored in

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