System Engineer 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 Mapping team at Lyft is tasked with building a digital representation of the physical world - a map. We collect and serve the freshest and most accurate mapping data possible, along with algorithms, models, platform services, and map-based user experiences that power Lyft’s current and future transportation offerings. Mapping represents a huge opportunity for Lyft’s business, but also a big challenge. We build and scale systems that deal with large data storage, real-time data processing, machine / deep learning pipelines, routing and ETA models, driver and passenger location tracking, and more. We built beautiful and magical user experiences on top of all those services, and compete with companies that have been in the mapping business for decades. Our engineering team is growing rapidly, and we are looking for Engineering Managers to help us scale. Our engineers are smart, flexible, and love solving difficult challenges. They look to their managers for organizational transparency, career development, mentorship, and honest feedback. They move fast and ship code to production continuously, relying on their leadership to increase productivity by removing obstacles and keeping processes lean. Responsibilities : Manage a rapidly growing team of engineers developing user-facing Mapping experiences Mentor and guide the professional and technical development of your team members. Help develop their careers and assign them to projects tailored to their skill levels, personalities, work styles, and professional goals Build teams that are collaborative, inclusive, and respectful of each other Provide continuous feedback, address underperformance, and recognize the individual strengths and contributions of your team members Create plans for prioritizing technical and resourcing challenges in y

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. Marketplace teams are at the heart of our products and decision-making, owning everything from rider pricing to driver earnings, incentives, and efficient matching. We’re looking for passionate, driven engineers to build systems that empower our riders and drivers to have the best transportation experience possible through prediction, adaptivity, and personalization. We’re looking for someone who is excited about working in a fast-paced, innovative, and impactful environment to create reliable solutions to distributed computing, ML, and data problems. The Pricing team is a centerpiece of Lyft’s Marketplace org, determining prices for all rideshare products and supporting new initiatives. Rider Engagement develops rider-facing engagement levers and optimizes user pricing experience to drive both short term and long term business outcomes. We work with Product & Science to solve and implement complex pricing requirements, balancing the needs of riders, drivers, and the business goals. As an owner of one of the most critical flows in the company, you will work on a wide array of challenges such as latency-sensitive concurrency problems, large scale distributed systems, and experimentation. If you’re interested in playing a large part in demand / supply management and improving the Lyft customer experience, this could be a great fit for you. Responsibilities: Drive high-impact projects and innovate new solutions to provide the best user experience. Work closely with cross-functional teams and partner teams to develop solutions based on technology and business needs, and advance team’s goals and priorities Independently lead features from idea to positive execution and launch Unblock, support and communicate with internal partners to achieve results Write well-crafted, well-tested, readable, maintaina

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. Our core philosophy is to empower developers to self-serve rather than be bottlenecked by a central quality team. We believe that by creating smart, automated tooling, we can eliminate common roadblocks, making developers happier and more productive. The Rider Quality team is focused on elevating quality, testing, and accessibility across our mobile platforms. We are currently shifting our strategy to heavily leverage automation and AI to revolutionize how we approach testing. We're not doing traditional QA - we're building the future of quality engineering. This is a chance to step into a Senior role where you won't just write code; you'll design systems that define how hundreds of engineers deliver product faster, happier, and with fewer bugs. We are fundamentally shifting away from manual processes and existing automation frameworks that struggle to keep up, betting heavily on Artificial Intelligence and agentic frameworks to drive a massive "shift left" in our organization. Success in this role is measured by tangible impact, including increased developer satisfaction, engineering hours saved, and bugs/incidents avoided in production. We are seeking a highly skilled and innovative Senior Software Engineer to join our team. You will be instrumental in building the next generation of our quality assurance platform. You will be responsible for designing and developing advanced AI-powered tooling for test case generation, review, and execution. Your work will directly impact our ability to provide fast, actionable feedback to developers, "shifting left" to ensure quality from the earliest stages of development. You will play a key role in integrating these tools into our existing developer workflows, ensuring seamless adoption and maximum impact. We are looking for someone with a strong background in

Engineering Manager, AI Conversation Platform 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 The newly formed Conversation Platform team aims to build a conversation platform for all merchants who use Stripe. We are doing so by (a) automating the easy tasks, and (b) assisting our users in the difficult tasks. Some examples include customizing the Stripe landing page to suggest bespoke integrations, allowing users to command the Stripe API in natural language, and resolving user issues automatically. We are developing RAG based systems on the latest LLMs as well as fine-tuning our own models. We’re an end-to-end team going from ideas to models to shipping in production. What you’ll do Responsibilities Driving an ambitious vision for AI/ML that benefits our users Setting the technical & process direction for the team based on business goals Brainstorm and coordinate product integrations with partner teams Proposing new ideas and building prototypes Be an integral part of a larger ML community internally & externally Hire & develop a world-class team to deliver high-quality ML systems. Coach engineers to help them grow in their careers and maintain a high bar Who you are We are looking for ML Engineering Managers who are passionate about using ML to improve products and delight customers. You have experience leading teams that develop streaming feature pipelines, build ML models, and deploy them to production, even if it involves making substantial changes to backend code. You a

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. The Opportunity: Okta Access Gateway (OAG) Enterprises run on a mix of modern cloud services and mission-critical on-premises systems (such as Oracle E-Business Suite, SAP, PeopleSoft, and custom legacy web apps). Okta Access Gateway (OAG) solves the enterprise hybrid cloud challenge by extending Okta’s cloud identity, Adaptive MFA, and Zero Trust security policies to on-premises and legacy applications without requiring custom code changes or traditional VPNs. As the Engineering Manager for Okta Access Gateway in Toronto, you will lead and grow a team of software engineers building the next generation of our hybrid access and gateway infrastructure. You will partner closely with Product Management, Architecture, Security, and Quality teams to deliver high-throughput, mission-critical security software deployed across multi-cloud and enterprise datacenters globally. What You’ll Do People Leadership & Team Growth Lead, mentor, and empower an engineering team, fostering an inclusive, high-performance, and psychologically safe engineering culture. Drive career progression, goal setting, regular 1:1s, and continuous feedback to help engineers grow their technical and leadership skills. Attract, interview, and hire diverse engineering talent to scale Okta’s engineering presence in Toronto. Delivery & Operational Excellence Own the end-to-end execution and delivery of key product roadmap initiatives, balancing feature velocity, technical debt, and softwar

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: 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 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

Overview: Qsight is a high-growth division of Guidepoint focused on building data intelligence solutions for the healthcare sector. Qsight leverages proprietary datasets and rigorous analysis of alternative data sources to generate actionable insights for top-tier institutional investors, medical device manufacturers, and pharmaceutical companies. The Qsight team develops market intelligence products designed to be highly relevant, accurate, and scalable – delivering superior insights to a diverse, global client base. We are seeking an experienced, motivated Tehnical Operations Engineer to join our growing team. This is a multiple-hats role focused on SaaS/platform operations and tier-2 support for client-facing systems. You will own the administration and reliability of key tools, troubleshoot and resolve escalations with clear documentation, and build lightweight automation and reporting to reduce manual work as we scale. You will partner closely with Customer Success, Product, and Engineering to proactively monitor, support, and improve critical systems. Through practical, creative problem-solving, you will strengthen reliability, accelerate time to resolution, and increase operational visibility. Day to day, you will triage and resolve client technical questions, manage vendor license administration and renewals, and produce reporting that informs operational decisions. This role is a launchpad toward an SRE/Platform Engineering track as you grow into deeper automation, reliability engineering, and systems design work. This is a hybrid position based out of our Toronto office. What You’ll Do: Platform Support Own routine ops and configuration changes for critical SaaS platforms – Including Tableau, Freshdesk, Datadog, and our own client facing and internal portals Configure and maintain Freshdesk portals, routing, SLAs, permissions, integrations, etc. based on business requirements. Automate manual operations with Python, PowerAutomate, and shell scri

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? This role is for people who love building tools for their coworkers. The Internal Applications team creates tools that help us create better models. In this role you will collaborate with internal stakeholders, which include annotators, ML researchers, product managers and more. Join our team of builders who create tooling that will pave the way for the next generation of large language models! As a Full-Stack Software Engineer on the Internal Applications team, you will: Work with a small talented and enthusiastic team of software engineers Contribute to delightful experiences for our user-facing products, meticulously crafting code for browsers and servers Collaborate and grow with your engineering colleagues of all levels through direct pairing sessions, architectural designs, documentation and talks Identify and remove roadblocks to enable your team to increase its engineering velocity. Build resilient systems that are mission-critical Keep up with the cutting edge and adopt new technologies to improve performance and reliability You may be a good fit if: You have experience shipping products with a large numb

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 Identity & Integrity organization is looking for software engineers. We are growing our team with people who want to build, improve and incorporate technologies that make the lives of our community more enriched and safe. 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. As a Software Engineer in the Identity team, your primary responsibilities will encompass: Lyft’s Login & Signup Experiences: Design and enhancement of our Multi-factor authentication (MFA) experiences. Optimization of verification funnels, including: Phone-based two-factor authentication (2FA) Email verification Identity provider single sign-ons (SSO) Overseeing session management and device validation. Developing OAuth client provisioning and related tooling. Account Security: Act as the frontline defense against fraudsters and phishers aiming to exploit rider and driver accounts through product vulnerabilities. Implement strategies to counteract risks posed by social engineering tactics. Scaling Core Services: Lead the maintenance and optimization of core microservices under the Identity team's purview, essential to Lyft’s diverse service offerings. Manage organizational structures and multi-user management systems. (RBAC, family accounts, AuthZ) Design solutions for high-stakes challenges such as: Preventing unauthorized driving. Thwarting abuse related to recycled phones and their numbers. Striking a balance between stringent customer verification and ensuring minimal user friction. Responsibilities Write well-crafted, well-tested, readable, maintainable code Promote appropriate tech and engineering best practices Implement identity and security protocols to se

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. Interns work side-by-side with top engineers in the industry while having autonomy from the get-go. They contribute to user-facing products and are able to see their work go live quickly. 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: Own your project, while checking in with other team members throughout the day with questions and updates You leave the code in a better state than when you found it (progressive refactor) You value reliability, ensured by testing (unit, integration and load tests) Participate in code reviews to ensure code quality and distribute knowledge Continuous integration and deployment Go home knowing that your work today is meaningfully improving the lives of every Lyft driver and every Lyft passenger! Experience: Currently pursuing a Bachelor's or Master's degree in Computer Science from a university in Canada (required) , with a graduation date between December 2027 and Summer 2028 (required). For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience Available during Summer 2027 for an internship in Toronto Strong knowledge of CS fundamentals Knowledge of Python, JavaScript, CSS, and HTML Experience working with leading JavaScript frameworks, like React Experience with modern frontend testing tools, such as Webpack, Babel, Jest, Jasmine, Protractor, and WebDriver Understanding of how browsers and DOM work Experience with Git or other distributed version control systems Experience with browser developer tools Experience with the Unix command line interface Solid understanding of web performance Experience with TypeScript Experience with CSS