Startup And Venture Ecosystem Lead in Canada

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. THE OPPORTUNITY Auth0 is a leading identity platform that secures billions of logins every year for organizations around the world. We're trusted by enterprises, startups, and developers to simplify identity and access management across any application, on any platform, anywhere. We're seeking a Product Operations Manager with a strong focus on data and analytics to help us turn raw data into meaningful business insights. Reporting to the Head of Product Operations, you'll be the person who looks at what the data is telling us and connects it to what it means for the business — revenue, retention, growth, and product direction. This is not a pure analyst role. You'll need to understand the business deeply enough to ask the right questions of the data, and communicate the answers in a way that drives real decisions. You're equally comfortable working in a dashboard as you are in a leadership meeting explaining what the numbers mean and why they matter. KEY RESPONSIBILITIES: Turning Data Into Business Insight: Take raw product and business data and translate it into clear narratives about what is working, what isn't, and where the opportunity lies. Build and maintain decks and dashboards that go beyond reporting numbers, telling a story and driving action. Work with Product to define the KPIs and metrics that matter most to the business and ensure teams understand how to track them, and how their work connects to those outcomes. Ident

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 Global Partner Engineering and Operations (PE&O) team is part of Stripe’s Global Partnerships organization and is responsible for managing the technical and operational aspects of new and existing product partnerships and programs. Positioned at the intersection of product, engineering, and partnerships, we focus on technical operational execution and optimization with financial ecosystem partners. We drive smooth technical onboarding and implementation with financial partners, we manage the ongoing engagement between Stripe and its partners, and we monitor and optimize stringent quality and performance targets. Our team also drives partner-agnostic programs and initiatives to address broad ecosystem challenges and builds technical solutions and tools that enhance operational efficiency and scalability. What you’ll do We are seeking a knowledgeable and proactive Technical Partner Manager to join our Global Partner Engineering & Operations (PE&O) Network partnerships team at Stripe. In this role, you will be responsible for building and maintaining strong relationships with our partners, facilitating technical integrations and launching new capabilities with new

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the architecture, design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborate with cross-functional teams to define, design, and deliver new features. Proactively identify opportunities for, and driving improvements to, current programming practices, including process enhancements and tool upgrades. Present technical information to teams and stakeholders, providing

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Identity Engineering team. In this role, you will help support the design and development of core software systems specifically focused on identity, access management, authorization, and authentication. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our identity infrastructure to ensure secure authentication and authorization across enterprise systems. Build software for authentication mechanisms such as Single Sign-On (SSO), Multi-Factor Authentication (MFA), and federated identity solutions (SAML, OAuth, OpenID Connect). Build software for authorization mechanisms such as Relation-based access control (ReBAC), Attribute-based access control (ABAC), Role-based access cont

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Identity Engineering team. In this role, you will help support the design and development of core software systems specifically focused on identity, access management, authorization, and authentication. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our identity infrastructure to ensure secure authentication and authorization across enterprise systems. Build software for authentication mechanisms such as Single Sign-On (SSO), Multi-Factor Authentication (MFA), and federated identity solutions (SAML, OAuth, OpenID Connect). Build software for authorization mechanisms such as Relation-based access control (ReBAC), Attribute-based access control (ABAC), Role-based access cont

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Platform Engineering team. In this role, you will support the design and development of shared platforms used across Scale. This includes designing our foundational data platforms and lifecycle, architecting Scale’s core cloud infrastructure and orchestration stack, and redefining how engineers develop, build, test, and deploy software at Scale. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our foundational platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements. Collaborating with cross-functional teams to define, design, and deliver new features. Proactively identifying opportunities for, and driving improvements to, current p

Chez Lyft, notre mission est de servir et de connecter. Nous visons à y parvenir en cultivant un environnement de travail où tous les membres de l'équipe ont leur place et peuvent s'épanouir. Les stagiaires travaillent côte à côte avec les meilleurs ingénieurs de l'industrie tout en ayant une autonomie dès le départ. Ils contribuent aux produits destinés aux utilisateurs et peuvent voir leur travail être mis en ligne rapidement. Lyft favorise un environnement collaboratif au bureau, donc il y a toujours un esprit vif désireux d'entendre parler de votre prochaine idée. Alors, quelle est la vôtre? Responsabilités: Prenez en charge votre projet, tout en échangeant avec les autres membres de l'équipe tout au long de la journée pour poser des questions et faire le point Vous laissez le code dans un meilleur état que vous ne l'avez trouvé (refactorisation progressive) Vous accordez de l'importance à la fiabilité, garantie par les tests (tests unitaires, d'intégration et de charge) Participez aux revues de code afin d'assurer la qualité du code et de partager les connaissances Intégration et déploiement continus Rentrez chez vous en sachant que votre travail d'aujourd'hui améliore concrètement la vie de chaque chauffeur et chaque passager Lyft Expérience: Poursuit actuellement un baccalauréat ou une maîtrise en informatique dans une université canadienne (obligatoire) , avec une date de graduation prévue entre décembre 2027 et l'été 2028 (obligatoire) . Pour les candidats à la maîtrise ayant travaillé entre leur baccalauréat et leur maîtrise : les candidats doivent également avoir moins de 2 ans d'expérience de travail à temps plein pertinente Disponible pendant l'été 2027 pour le stage à Montréal Solides connaissances des fondamentaux de l'informatique Excellentes compétences en communication Passion pour la communauté, la durabilité et/ou le transport Capacité à s'épanouir dans un environnement d'entreprise en démarrage (startup) Contributio