Machine Learning Intern 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. 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

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

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 Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree at a university in Canada (required) in mathematical sciences ( Opera

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

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

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

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

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team of bold thinkers and sharp problem-solvers who are wired to make an impact. The Ops Platform organization develops internal platforms that replace repetitive manual processes with AI-driven systems. These tools support key areas such as Fraud Operations, Account Operations, Financial Crimes Operations, and Retirement Services. The team works closely with product, data science, and operations partners to deliver reliable systems that improve decision-making and efficiency! As a Software Developer, you will design and build platforms that enable operational teams to investigate and resolve issues more quickly and accurately. You will work with large datasets and signals to create tooling that supports fraud investigation and other operational workflows. You will collaborate with data scientists and machine learning engineers to translate manual processes into automated systems. Your work will focus on improving system reliability, reducing operational effort, and increasing the speed at which new products and features can be supported across Robinhood’s offerings. This role is based in our Toronto, ON office, with in-person attendance expected at least 3 days per week. At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams. What you’ll do You will define technical direction and make architectural decisions for systems that support operational workflows across multiple product lines You will build tools that proces

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 role At Okta, we believe AI will fundamentally transform how design, research, and product development happen. We are looking for a Senior Design Operations Program Manager, Agentic Design to lead the operationalization and enablement of internal AI agents, plug-ins, and automated workflows across our Design team — reimaging how designers create in the AI era through internal AI agents. In this role, you will bridge the gap between AI tooling capabilities and practical design ops execution. You will partner closely with design, product management and design systems to govern, evaluate, deploy, and scale AI-driven design capabilities — making our 60+ person design org dramatically faster, more consistent, and highly innovative. This is a tactical, execution-focused builder role for an operations leader who is deeply curious about AI tools, understands modern UX workflows, and excels at change management, team enablement, and operationalizing new frameworks. What you'll do AI & Agentic Design Enablement Serve as the operational connective tissue driving AI adoption, evaluation, and workflow integration across Product Design, UX Research, and Content Design. Manage the intake, evaluation, and approval process for design plug-ins, Model Context Protocol (MCP) integrations, and generative AI tools (e.g., custom content design assistants, design-to-code agents). Partner with internal engineering teams to operationalize, ship, and drive adopt

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. Position Description: You will proactively construct and own an AI-forward research roadmap for key product pillars at Okta, operating at the intersection of Identity, Security, and Artificial Intelligence. As a Staff-level individual contributor, you will drive both qualitative and quantitative methodologies to define user experiences for non-deterministic AI agents, automated workflows, and enterprise platforms. Additionally, you leverage agentic tools and AI workflows internally to scale qualitative coding, synthesis, and research operations across the organization. In this role, you’ll get to: Drive Product-shaping Research: Lead foundational and evaluative research to inform strategic and tactical product decisions. Execute Balanced Mixed-Methods: Drive qualitative depth (contextual inquiry, cognitive walkthroughs) and quantitative rigor (large-scale surveys, behavioral telemetry, statistical modeling) to evaluate AI products. Pioneer AI Research Operations: Integrate AI tools, prompt engineering, and agentic research workflows into your daily practice to accelerate quality research outputs. Lead Cross-Discipline Collaboration: Facilitate research to drive cross-discipline clarity, executive alignment, and decision-making across complex security and admin workflows. Solve Complex Problems: Bring stakeholders together across multiple teams to scope problems and collaborate on research in ways that nurture a culture of curiosity and learning. Cultivate E

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team, applying frontier technologies to the world's biggest financial problems. We're looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn't a place for complacency, it's where ambitious people do the best work of their careers. We're a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. Our Core Data Engineering team is responsible for designing and building all foundational datasets used across Robinhood and within our operational business areas. We build the foundational data models and core data layers that are consumed by downstream users, ensuring high data quality and reliability. We also develop internal data and AI tooling that enables teams across the company to scale their data development workflows efficiently. Our team collaborates with engineering, product, brokerage, crypto, and marketing teams to expand and grow Robinhood's products around the world ! We also partner with Machine Learning teams to build robust training datasets that power intelligent product features. As the Engineering Manager for our Toronto Data Engineering team, you will lead a team of exceptional engineers and drive the execution of key data initiatives. In this role, you will balance technical leadership with people management, dedicating approximately 60% of your time coaching and 40% to hands-on technical contributions, such as code and architecture reviews. You will drive roadmap planning and establish clear goals for the team, particularly as we expand into new mark

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit’s Ads Data Science team is looking for a Senior Staff Data Scientist to lead the scientific strategy behind Reddit’s ads measurement and signal systems. This role sits at the center of how Reddit proves advertiser value, improves signal quality, builds privacy-aware measurement systems, and connects ads exposure to real advertiser outcomes. As a Senior Staff Data Scientist for Ads Measurement, you will be the principal architect of our technical vision and the driving force behind the next generation of our measurement ecosystem. In a landscape rapidly shifting due to privacy regulations, browser changes, and evolving platform dynamics, you will spearhead innovation across experimental design (incrementality/lift), identity, signals, and privacy-safe 1P/3P measurement. This is a high-visibility, high-impact role requiring a rare blend of deep experimentation & causal inference expertise, strategic foresight, and the ability to influence cross-functional executives and industry standards. You will not just adapt to the changing ad-tech environment, you will redefine how we measure value. Responsibilities Technical Vision & Strategy: Define the long-term data science vision & strategy across ads measurement, signal quality, identity, attribution, and privacy. Establish how Reddit should evaluate advertiser value, measurement quality, and signal utility across first-party and third-party products. Set the Cross-Pillar Measurement Science Strategy: Define the long-term data science strategy across a

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit’s Ads Data Science team is looking for a highly experienced Staff Data Scientist to advance the intelligence powering the advertiser experience on Reddit. In this role, you'll take deep ownership of a high-impact problem space within advertising, specializing in measurement, identity, and signal quality. This is a high-impact, high-autonomy role where you'll influence strategic direction, set a high technical bar, and drive cross-functional initiatives across one or more critical focus areas in the Ads organization. Responsibilities: Design the Future of Ads Identity: Develop/employ probabilistic models for identity resolution. Design the methodology that links on-platform and off-platform actions to maximize addressability while honoring privacy. Advance Lift Methodologies & Experimentation: Own the statistical rigor behind Reddit’s Brand and Conversion Lift products. Innovate experimental design and develop infrastructure that supports large-scale, high-velocity, low-bias testing for advertisers. Maximize Signal for Predictive Performance: Define the strategy for new signal sources. You will mathematically quantify the value of these signals and work with modeling teams to incorporate them into predictive models, directly improving bidding efficiency and ROAS. Define Ground Truth & Evaluation Frameworks: Solve the industry-wide challenge of validating identity and measurement. Design the objective functions and truth sets used to train our models and measure the incremental impact of our identity graph.

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. This is a contract position through our staffing partner Magnit. 108,000.00 - 135,000.00 - 162,000.00 CAD Annual This role is not eligible for the Okta-sponsored benefits listed below. Magnit will provide any locally required benefits. Okta seeks a skilled Senior Recruiter to drive full-lifecycle recruitment and build strategic talent pipelines for our Engineering organization across North America. As part of our AMER Tech Recruiting team, you will be a trusted talent advisor responsible for sourcing, engaging, and delivering top-tier engineering talent while maintaining an "always recruiting" mindset in a fast-paced, high-growth environment. What You'll Be Doing Own full-lifecycle recruitment for Engineering and technical roles (Software Engineering, Site Reliability, Security, TPM, Product) across US & Canada, managing a flexible req load that scales with business priorities. Partner strategically with hiring managers and leadership to understand talent needs, define role scope, advise on talent gap mitigation, and challenge assumptions to ensure hiring decisions strengthen long-term organizational capability. Build and execute talent strategies that balance external hiring with internal mobility, creating sustainable pipelines that reflect commitment to diversity, inclusion, and high-performing engineering culture. Drive metrics-informed recruiting decisions by developing KPIs, analyzing recruiting data, and using insights to optimi

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. As the Advocacy & Content Strategist, you will serve as the program architect and content engine that mobilizes Okta and Auth0 experts, customers, partners, developers, and security practitioners into vocal brand advocates. Operating as an individual contributor within Customer Acceleration, you are responsible for building structured customer programs and co-creating content with power users that amplify our post-sales experiences across learning, badging, certification, support and customer success, while driving product adoption and customer success. Job Duties and Re sponsibilities Scale & Activate Customer Champions: Operationalize and grow structured advocacy frameworks, like the Champions Program, complete with badging milestones, gamified recognition, and tiered perks that incentivize long-term participation. Build repeatable processes to systematically surface champion expertise and route these user voices into high-impact content formats, GTM initiatives, and key business moments. Co-Create Content with Technical Users: Partner directly with internal, partner and customer champions, developers, and practitioners to co-produce user-generated content (UGC), technical deep-dives, AMAs, expert Q&As, and customer-led blogs. Develop Customer Success Storytelling: Identify, interview, and write compelling customer success stories, case studies, and advocate spotlights that prove the business value of our post-sales experiences (E