Primary Care Physician 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 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. Agentic AI is at the center of how we scale that mission. We fine-tune and align open-source models, build AI-powered support agents, and develop end-to-end AI agents for safety case management, systems that reason over complex, high-stakes cases and drive them to resolution. SCC brings together ML, data, backend, and product engineers alongside data scientists and operations partners to transform these systems. As a Machine Learning Engineer on the SCC team, you will fine-tune and align models and build AI Agents that power how riders and drivers get help. Your work spans the full loop: post-training open-source models for our domain, composing them into multi-step agents, and building the evaluation that proves they are safe to ship in a customer-facing, safety-critical setting. Post-train and adapt open-source LLMs for SCC use cases using SFT, LoRA, and preference-tuning methods (RLHF, RLAIF, RLVR). Design and build AI-powered support agents and end-to-end agents for safety case management using LangGraph or equivalent agentic frameworks. Own the evaluation data flywheel, offline and online, that defines what "good" looks like and build benchmarks for the team to hill-climb. Turn interaction feedback into training data and learning signals, closing the data flywheel that continuously improves the models. Responsibilities: Conduct literature review and build post-training fra

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's Customer Care Operations organization manages over 1.7 million monthly customer interactions and serves as the company's primary direct touchpoint with riders, drivers, and businesses — spanning frontline support across multiple customer segments, a global BPO workforce, and the central functions that enable them to operate at scale. The Senior Manager of Support Excellence owns the enablement infrastructure that determines whether Lyft's support operation can scale efficiently, react nimbly, and maintain high standards: Knowledge Management, Quality, Learning & Performance, and Tooling Enablement. This is not a role for someone who wants to maintain and optimize — it's a role for someone who wants to reimagine. The right person brings a bold, integrated vision for how these functions work together with Operations, Product, and Technology to improve customer outcomes and accelerate Lyft's evolution into an AI-native, human-enhanced support organization. They will set the direction, hold the bar, and move at the pace the environment demands — with the industry expertise to know what "great" looks like and the conviction to pursue it. Reporting to the Director of Business Planning & Central Operations, this role leads a team of 4-6 direct reports and 40-50 indirects, each owning a distinct function on the team team. Responsibilities: Vision & Strategy Define and own an ambitious, integrated vision for how Knowledge Management, Quality, Learning & Performance, and Tooling Enablement work together — not as separate functions, but as a unified enablement system that improves customer outcomes and advances Lyft's AI-native support evolution. Expand active AI fluency to every function in the portfolio — from how knowledge is structured for AI retrieval, to how quality signals feed mod

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 Engineer on the SCC team, you will have ownership over the data modeling and pipelines that power SCC’s Associate and AI Agent Platform . Your efforts will be critical to the reliability of our pipelines, execution of third party data integrations, accurate reporting of agents performance, and efficiency improvements that can save millions of dollars / year. You will work cross-functionally to bridge Lyft's business goals with data engineering. Your efforts will allow access to business and user behavior insights, using huge amounts of Lyft data to fuel several teams such as Analytics, Data Science, Engineering, and many others. Responsibilities: Owner of the core data pipeline, responsible for scaling up data processing flow to meet the rapid data growth at Lyft Evolve data model and data schema based on business and engineering needs Implement systems tracking data quality and consistency Develop tools supporting self-service data pipeline management (ETL) SQL and MapReduce job tuning to improve data processing performance Write well-crafted, well-tested, readable, maintainable code Participate in code reviews to ensure code quality and distribute knowledge Collaborate cross-functionally with product, engineering, data science, and marketing teams to understand business problems and align on prioritization and solutions Experience: Bachelor's degree in Compute

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. Sitting within the broader Safety & Customer Care team, Lyft's Customer Care Operations organization manages over 1.7 million monthly customer interactions and serves as the company's primary direct touchpoint with riders, drivers, and businesses — spanning frontline support across multiple customer segments, a global BPO workforce, and the central functions that enable them to operate at scale. The Director of Business Planning & Central Operations is a newly created role at the center of how Customer Care runs and grows. This leader will ensure the org is resourced and positioned for the future, and will own the functions that keep Customer Care financially disciplined and execution-ready. Reporting to the Senior Director of Customer Care Operations, they will lead five functions: Planning & Forecasting, Workforce Management, Readiness & Integration, Vendor Management, and Support Excellence. What You'll Do Business Planning & Strategy Partner with the Senior Director to drive H1 and H2 planning — translating annual objectives into operational plans, investment decisions, and resource models. Lead the investment brief process: sizing opportunities, articulating trade-offs, and building the business cases that secure resourcing for strategic priorities. Drive capacity planning, scenario modeling, and long-range forecasting to ensure the internal and external workforce scales efficiently alongside platform growth and AI adoption. Define and operationalize OKRs across the portfolio, then build the rhythms and infrastructure — scorecards, business reviews, and performance dashboards — that hold teams accountable and give leadership clear visibility into progress and outcomes. Growth & Integrations Lead operational readiness for major product launches, external partnerships, and

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role Commercial Account Managers at Ramp are the primary relationship owners post-implementation, responsible for driving product adoption, spend activation, and long-term account growth across a portfolio of 150–200 commercial customers. As Ramp’s first Account Manager dedicated to Canadian-based customers, you’ll own a portfolio of Canadian commercial accounts; deepening relationships, leading strategic conversations, and identifying opportunities to expand Ramp’s footprint while developing a deep understanding of their local needs and helping shape Ramp’s growing presence in Canada. What You’ll Do Build and nurture strong relationships across new and existing high-value commercial customers to better achieve their needs and manage all reporting of health within accounts Develop deep, multi-threaded relationships with decision makers at your customers Drive spend across your book of business by owning retention, adoption, expansion within existing products, and growth across your your accounts Lead Executive Business Reviews within your

ROLE: SENIOR FINANCE MANAGER LOCATION: TORONTO The Role Salt XC is looking for a Senior Finance Manager to lead the day-to-day financial management of The Kitchen, a large-scale embedded agency partnership with a Fortune 500 client. This role will be the primary Finance partner and point of contact for The Kitchen. While Salt’s broader Finance team will continue to execute transaction processing, including payroll, accounts payable, accounts receivable and expense processing, this person will sit at the centre of the operation—ensuring projects are financially controlled, billings happen on time, revenue and costs are appropriately recognized, reporting is accurate, and stakeholders have clear and timely visibility into the financial health of the business. This is an ideal role for someone with strong project accounting and revenue accounting experience who is equally comfortable working with Finance teams, agency operators, producers and senior client stakeholders. Key Responsibilities Project & Financial Management • Own the financial oversight of approximately 100-150 client projects annually • Maintain accurate project financials, including budgets, committed costs, actual costs, billings and project-level profitability • Ensure production costs and employee expenses are accurately captured and allocated to the appropriate projects • Monitor project financial activity from initiation through final reconciliation and close • Identify financial discrepancies, aging items and project risks and proactively drive them to resolution • Maintain strong financial controls while supporting the speed and flexibility required in an agency environment • Identify areas for efficiency and cost reductions Revenue, Billing & PO Management • Own the financial workflow between project teams, both internal and external, to ensure projects are billed accurately and on tim

Overview: Guidepoint seeks an experienced Data/AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The Senior AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization

Overview: Guidepoint seeks an experienced AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization in production

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. With over half a billion rides and counting, Lyft is solving hard problems in a flourishing domain with a lot of data and creative solutions in Marketplace, Mapping, Fraud, Growth and beyond. We're actively building the next-generation Machine Learning (ML) platform for low-cost, ultra-immersive transportation to improve people’s lives using modern ML with peta-byte scale data. Our Machine Learning Engineers are excited to work on these challenging problems and redefine solutions to directly impact various aspects of Lyft's primary business. If you are a student with experience in machine learning workflows, passionate about solving challenging problems using data and working in a dynamic, creative, and collaborative environment, this opportunity is for you! Responsibilities: Contribute to the design, build, train and test of Machine Learning models Write production-level code to convert ML models into working pipelines Partner with Product Managers, Data Scientists, and fellow ML Engineers to frame Machine Learning problems within the business context Analyze experimental and observational data, communicate findings to support decisions Participate in code and spec reviews to ensure code quality and distribute knowledge Experience: Currently pursuing a Bachelor's, Master's, or PhD degree in Computer Science or a related technical field 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 the internship in Toronto Good understanding and knowledge of ML libraries like scikit-learn, Tensorflow, PyTorch, Keras, MXNet, et

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role The Events Analytics Platform (EAP) team is responsible for the infrastructure that powers all of Sentry's time-series data and searching capabilities across billions of events with sub-second latency. We started this initiative by building Snuba, the primary storage and query service for Sentry's event data powered by ClickHouse, and we are now focused on unlocking deeper visibility and reporting across the terabytes of event data our users generate. As a Senior Software Engineer, you will lead efforts to push the boundaries of data visibility at Sentry. You will do this by expanding the capabilities of our search infrastructure, building new capabilities on top of our state-of-the-art storage layer and increasing the performance and integrity of Sentry’s core data services. You will also help shape Infrastructure's technical direction at Sentry and collaborate with Product and other Engineering teams to turn that vision into a reality. If you want to solve the hard problems that come with scaling event data into the petabyte range, this could be the job for you. In this role you will: Expand EAP's ability to deliver data at world-class speed and reliability. Architect and automate services and systems to scale reliably under growing demand. Make architectural trade-offs that balance product requirements with engineering constraints. Maintain and grow the team's code quality initiatives by regularly reviewing code and contributing to design decisions. Lead design and discussions around deliverables the team is working towards. Improve the maintainability and developer experience of the codebases EAP owns. Exa

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role Issue Workflow is Sentry's primary product surface. Our issue platform processes billions events daily and turns them into actionable insights that help millions of developers fix bugs faster. As a Staff Software Engineer on the Issue Workflow team, you'll architect the systems that power this experience. You'll work at the intersection of high-scale distributed systems and product engineering, building real-time data pipelines, search backends, and analysis systems that surface signal from noise. This is product engineering at massive scale—where every architectural decision impacts millions of debugging sessions. You'll be the technical leader who shapes how Sentry groups issues, how we make search lightning-fast, how we enable sophisticated agentic workflows, and how we ensure that the product is performant even at billions-of-events scale. Your work will define what's possible for the most trafficked part of Sentry's platform. In this role you will Drive technical strategy and roadmap. Partner with engineering leadership, product, and design to shape the multi-quarter technical vision for Issue Workflow platform. Make strategic calls about architectural direction, technology choices, and technical debt. Ensure the team is building a strong foundation to scale with Sentry's growth. Solve complex performance and scalability challenges. Champion product quality and user experience. Build features that don't just work—they delight. You understand that milliseconds matter in the developer experience. You sweat the details of interfaces, error messages, loading states, and edge cases. You instrument everything s

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 hiring a Senior Financial Data Analyst to lead the Reporting sub-team within Finance Data & Insights. This sub-team is core to ensuring all key Run the Business (RTB) financial reports are complete, accurate, and operationally reliable on a day-to-day basis. The mandate is two-fold: build repeatable systems, playbooks, and documented workflows that reduce reactive work, and own the primary stakeholder relationships for RTB work across teams. This is a high-visibility role that combines hands-on ownership of critical reporting with team leadership and process-building. Responsibilities: Own all RTB and Compliance reporting (tax, airports, audit requests, etc.), ensuring accuracy, completeness, and operational reliability Build and maintain process documentation, checklists, and operational playbooks that make reporting workflows repeatable and resilient Receive and operationalize reports stabilized by Finance Data Products, integrating them into day-to-day RTB reporting operations Reduce fire-drill, ad-hoc response patterns by replacing them with documented, recurring workflows and automation Identify and drive automation opportunities across RTB reporting processes to improve efficiency, reduce manual effort, and further reduce ad-hoc work Own primary stakeholder relationships for RTB work, serving as the go-to point of contact across teams Lead large-scale, cross-functional initiatives with significant autonomy — from problem definition through execution — proactively communicating progress and risks to stakeholders and management Proactively identify risks, gaps, and opportunities for improvement within RTB reporting and drive initiatives to address them Experience: BA/BS with 5+ years of experience in finance, accounting, business, consulting, or analytics Advanced proficiency in

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 People Analytics team at Lyft exists to build data trust — turning people data into clear, reliable insights that help our HR Business Partners, talent leaders, and executives make better decisions. We're a small, high-impact team in the middle of a meaningful BI transformation: we recently moved to ThoughtSpot as our primary analytics platform, and we're not just replicating old dashboards — we're rethinking what self-service analytics looks like for a People team. That includes exploring ThoughtSpot's AI capabilities to surface proactive insights, enable natural language querying, and reduce the friction between a business question and a data answer. There's real greenfield work here, and we're looking for someone who wants to help define what AI-powered people analytics looks like at Lyft. We're looking for a Data Analyst to join our People Analytics team, based in Toronto. You'll report to the Senior Manager, People Analytics and serve as the first point of contact for incoming data requests across the People organization — triaging, scoping, and delivering on analytical needs ranging from quick ad-hoc pulls to fully built ThoughtSpot dashboards. This role is well-timed: you'll be joining as we complete our migration from Tableau to ThoughtSpot, which means you'll have genuine influence over how we build our reporting layer and push into ThoughtSpot's AI features — think natural language search, AI-generated insights, and proactive anomaly detection applied to people data. This isn't a "maintain the dashboard" role. It's a chance to help build something new. You'll be a self-starter who is equally comfortable writing SQL and presenting findings to a VP. Responsibilities: Serve as the first point of contact for incoming data requests from across the People organization — scoping needs, setting