Jobs in Canada

Member Of Executive Operations in Toronto

98 active opportunities · Updated October 2026

Explore current member of executive operations jobs in Toronto. Filter by work mode, employment type, experience, department, date posted and distance.

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📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$46/hr

Quick readStrong listing-quality and freshness signals

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

PythonMachine LearningAIGo
L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$102K/yr

Quick readStrong listing-quality and freshness signals

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 is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our products and make business decisions. This will involve performing rigorous product deep dives, identifying opportunities for product enhancements, and measuring the impact of product changes. The Airports team, within the Driver organization, focuses on the airport marketplace and the unique products designed for this use case. Airports are one of the most important, impactful, and complex parts of Lyft’s Rideshare business, as they are a key part of both the rider and driver Lyft experience and have unique dynamics. As an Analytics Lead on the Airport team, you will collaborate with our team of engineers, product managers, and designers to conduct thorough data deep dives on airport performance, challenge our current strategy, and recommend enhancements to facilitate market growth. The ideal candidate can apply strong business acumen to propose product and marketplace changes, and is comfortable working with a highly cross functional team. In this role, you will help us tackle problems such as: How should we determine pricing and earnings for airport rides? Who are our current airport drivers and what segment can we focus on to grow our supply? How does this strategy interact with driver bonuses? Which airports are underperforming and which key metrics can we use to identify and classify airport performance? What targets should we set for these key metrics and how do we efficiently monitor these metrics? What is driving high cancellation rates today and which types of riders/drivers are cancelling? What product changes can we implement to reduce cancellation rates? How are riders and drivers using different ride modes at airports, and how do we design

L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$108K/yr

Quick readStrong listing-quality and freshness signals

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 Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our products and make business decisions. This will involve identifying and scoping opportunities, shaping team priorities, recommending and implementing technical solutions, designing experiments, and measuring the impact of new features. The Airports team, within the Driver organization, focuses on the airport marketplace and the unique products designed for this use case. Airports are one of the most important, impactful, and complex parts of Lyft’s Rideshare business, as they are a key part of both the rider and driver Lyft experience and have unique dynamics. As a Data Scientist on the Airport team, you will collaborate with our team of engineers, product managers, and designers to think critically about the current rider and driver experience and implement product enhancements to facilitate market growth. The ideal candidate can apply strong business acumen to propose product changes, develop end-to-end technical solutions, and is comfortable working with a highly cross functional team. In this role, you will help us tackle problems such as: What rider segments are present at airports and how can we address their major pain points to grow our airport marketshare? What new airport product features can we introduce to grow rider demand? Are we able to forecast rider demand and use this prediction to adjust ride offerings or improve the rider experience? How can we optimize ride offerings for each rider to maximize conversion? Responsibilities Define and implement decision frameworks, measurement strategies, and scientific methodologies that bring consistency and rigor to business decisions and forecasts, balancing opportunity and uncertainty Desi

PythonSQLAIGo
L
📍 Toronto, Canada
✓ Quality checkedCompany trend -72.4%

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 Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges - from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. Driver Incentives Science owns the algorithms and systems behind incentive design, influencing driver engagement and marketplace efficiency — from real-time supply positioning to longer-horizon earnings and engagement programs. The team is responsible for designing pay and incentive mechanisms that are efficient and good for driver experience over the long run. As a Data Scientist specializing in Algorithms, you'll partner closely with product, engineering, and operations leaders to build and scale incentive systems, shape long-term mechanism design strategy, and deliver on critical business goals tied to marketplace efficiency and driver earnings. Candidates with strong optimization backgrounds — think mathematical programming, control theory, or operations research — are a great fit, though we welcome strong candidates from machine learning or causal inference as well. The ideal candidate thrives in a fast-paced environment and brings a hands-on, entrepreneurial mindset to drive results. Responsibilities: Collaborate with engineering and product teams to design, implement, and iterate on new features and algorithmic improvements for driver incentives and pay mechanisms. Design, develop, and deploy optimization models, algorithms, and systems for problems such as budget allocation, multidimensional cost-curve development, and incentive targeting. Write production model code; collabor

PythonMachine LearningArtificial Intelligence
L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$108K/yr

Quick readStrong listing-quality and freshness signals

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 Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges - from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. Driver Incentives Science owns the algorithms and systems behind incentive design, influencing driver engagement and marketplace efficiency — from real-time supply positioning to longer-horizon earnings and engagement programs. The team is responsible for designing pay and incentive mechanisms that are efficient and good for driver experience over the long run. As a Data Scientist specializing in Algorithms, you'll partner closely with product, engineering, and operations leaders to build and scale incentive systems, shape long-term mechanism design strategy, and deliver on critical business goals tied to marketplace efficiency and driver earnings. Candidates with strong optimization backgrounds — think mathematical programming, control theory, or operations research — are a great fit, though we welcome strong candidates from machine learning or causal inference as well. The ideal candidate thrives in a fast-paced environment and brings a hands-on, entrepreneurial mindset to drive results. Responsibilities: Collaborate with engineering and product teams to design, implement, and iterate on new features and algorithmic improvements for driver incentives and pay mechanisms. Design, develop, and deploy optimization models, algorithms, and systems for problems such as budget allocation, multidimensional cost-curve development, and incentive targeting. Write production model code; collabor

PythonMachine LearningAIGo
L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$108K/yr

Quick readStrong listing-quality and freshness signals

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. To fulfill Lyft’s mission of creating the real-time transportation network of the future, Lyft needs engineers from a scope of disciplines. We need engineers to help us intelligently scale our backend infrastructure, to increase pricing in real time given localized supply and demand data, to predict future localized demand, to create delightful and intuitive UX flows for passengers and drivers, to improve our cloud infrastructure orchestration and monitoring, to increase dispatched driver-passenger pairings based on real-time data and real-world edge cases, to build tools to increase the efficiency of our customer service team, and more. You're an enthusiastic and experienced app developer looking to take your skills to the next level by joining our iOS team. You’re excited about scaling millions of lines of Swift code and hundreds of mobile developers. Our app is used by millions of people, and we take great pride in our work. This means excellent development practices, careful code architecture, and an organization built around rapid releases. Our codebase is written entirely in Swift with modern design patterns and coding standards. We rely on 3rd party libraries and contribute back to the community (including the Swift language itself). Responsibilities Help establish roadmap and architecture based on technology and our needs Write well-crafted, well-tested, readable, maintainable code Participate in code reviews to ensure code quality and distribute knowledge Share your knowledge by giving brown bags, tech talks, and promoting appropriate tech and engineering best practices Performing thoughtful code reviews for colleagues, and help others by conducting high-quality code reviews Participate in hiring activities: take part in technical interviews, live coding, share detailed feedback to hir

ReactAISwiftExcel
L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$1.4M/yr

Quick readStrong listing-quality and freshness signals

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

PythonMachine LearningAIGo
L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$129K/yr

Quick readStrong listing-quality and freshness signals

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 is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our products and make business decisions. This will involve performing rigorous product deep dives, identifying opportunities for product enhancements, and measuring the impact of new features. The Global Growth organization is chartering the future for Lyft’s growth, focused on expanding Lyft beyond North American rideshare’s core products. This includes our premium Luxury modes and Livery drivers, building a unified Lyft presence internationally, and enabling Autonomous Vehicles (AVs) domestically and abroad. These teams are at the center of innovation and the future of Lyft’s growth, and this role would be directly shaping the strategic roadmap for these crucial areas. As a Senior Analyst, you will collaborate with our world class team of engineers, product managers, and designers to build the roadmap for business and product expansion to meet the needs of our international customers. The ideal candidate is a thought leader in this space, working across multiple functions and geographies. This role blends strong business acumen, marketplace dynamics, and strategic understanding of regulatory landscapes to craft a vision for Lyft around the globe. This role will help define Lyft’s strategy for where and how Lyft expands its footprint around the world, sizes the opportunity, scopes the unique products required, and is a liaison to our central marketplace teams. In this role, you will help us tackle problems such as: How will global expansion impact our current North American rideshare users? How does the competitive landscape in future geographies impact our growth strategy? What product developments do we need to develop to successfully expand and gain market share? H

L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$216K/yr

Quick readStrong listing-quality and freshness signals

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

L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$118.8K/yr

Quick readStrong listing-quality and freshness signals

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

AWSMachine LearningAIGo
L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$108K/yr

Quick readStrong listing-quality and freshness signals

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 transport network serves the needs of millions of people every day who want to get from one place to another using Lyft cars, bikes and scooters, with public transportation, or on foot in the most efficient way. To serve these needs, we need to suggest the fastest, most affordable and safest routes. We achieve this by processing millions of rides, taking into account the latest traffic information and analyzing the preferences of drivers. To strengthen our efforts, we are hiring a Software Engineer who will work on improving our routing engine, on building cloud-based services that can process millions of route requests per day and on creating workflows to process and analyze the data collected from our rides. For this we are looking for someone who has a strong background in software architecture and algorithms and understands at the same time how to build efficient data processing pipelines. Our technology stack is based on the latest technologies such as AWS, Kubernetes, Apache Airflow, Flink, and Kafka. We use AI and machine learning to improve development productivity, optimize customer support workflows, and enhance operational efficiency — all without compromising code quality or security. You will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on projects that delight millions of passengers and drivers. Responsibilities: Drive high-impact projects and innovate new solutions to provide the best routing experience possible Build and deploy mission critical algorithms and services that can serve millions of requests per day (backend and data-streaming services written in C++, Go, and Python) Analyze rides, understand customer pain points, prioritize and size feature requests and help design solutions based on o

PythonAWSAzureGCP
L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$102K/yr

Quick readStrong listing-quality and freshness signals

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

PythonSQLAIGo
SX
📍 Toronto, Canada· Full-time
✓ High-confidence listing

From $60K/yr

Quick readStrong listing-quality and freshness signals

ROLE: MEDIA SPECIALIST TEAM: MEDIA LOCATION: TORONTO - HYBRID ONSITE 2X/WEEK COMPANY OVERVIEW At Salt Media , we're on a mission to earn the world's attention. As the media division of Salt XC, we're building a different kind of agency where media, commerce, creative, data and technology work as a single connected team. Our people combine strategic thinking with AI-powered tools, automation and advanced analytics to help some of North America's most recognized brands solve complex business challenges and drive measurable growth. We move quickly, challenge convention, and believe the best ideas come from curious people who are empowered to experiment. If you're looking to do career-defining work alongside smart, ambitious teammates in an environment that's shaping the future of media, we'd love to meet you. ROLE OVERVIEW The Media Specialist will work across an exciting mix of clients in the CPG, Retail & Banking industries providing day to day support to the wider media team, with a focus on implementation and reporting. You will need to be highly proficient in media implementation, reporting and analysis. This includes a strong understanding of Social Media platforms, Google Analytics and Google Ad Words. You will need to develop strong trust-based relationships with both the client and agency team members. CORE RESPONSIBILITIES Work directly with the Media Supervisor to heavily support implementation, optimization & reporting for all key clients Work directly with the Media Supervisor to assist with overall client planning & day to day client requests Work directly with all media vendors to book, implement and report on campaigns With direction from the Media Supervisor support the preparation, writing and presentation of integrated media plans, proposals and analysis that satisfy client objectives and that go beyond the brief Maintain stewardship and accountability of the media plan,

GitAIGoRust
L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$108K/yr

Quick readStrong listing-quality and freshness signals

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

PythonJavaAWSGCP
L
📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$136K/yr

Quick readStrong listing-quality and freshness signals

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 Infrastructure team is passionate about building software to solve problems at massive scale. We do this often, and when we believe our solution is worth sharing with the community, such as Envoy Proxy , we open source our ideas for the benefit of others. As a Infrastructure Engineer at Lyft, you will run our Production Infrastructure by monitoring system availability and take a holistic view of our platform health. You will build software and platforms to automate infrastructure platform operations and management. By measuring and monitoring our operations you will seek opportunities to optimize our systems in order to push our platform forward, anticipating our customers' needs in order to continually improve the platform. You will provide Lyft partner teams with operational support to help them build robust large scale distributed systems. About the Team Data Pipelines is at the heart of all critical data flowing through Lyft supporting hundreds of services that impact millions of drivers and passengers every day. Our team’s mission is to empower Lyft engineers to self-serve in building and maintaining data pipelines as needed to support products that deliver the world’s best transportation experience. We leverage a variety of technologies to store, stream and manage data making it available to our internal customers. Responsibilities: Maintain and analyze metrics from; operating systems; control planes; and applications to assist in fault detection and performance enhancement Design, develop and deploy tooling and systems that continually improve the reliability, scalability and efficiency of our platform Balance feature development speed and reliability with service-level objectives Operate and improve our Infrastructure using industry best practices and tools Participate in design and

PythonAWSDockerKubernetes
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