Product Management Manager Merchant Lending in Canada

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? This role will focus on evaluating coding tasks, requiring you to review and debug code, navigate repository architecture, and analyze model trajectories. Your work will contribute to our model development efforts and the logic our models apply when completing task requests. Please note : This is a part-time independent contractor position available within Canada. We seek candidates who are able to commit to 16 hours per week minimum at a 40 CAD/hour contract rate. This role is BYOD 💻 - Bring Your Own Device (laptop). Remote work within Canada. 12 month contract. Performance incentives included! As a Data Annotation Specialist, you will: Evaluate the model's ability to respond to coding requests, workflows, and code base-related questions using available tools. Assess agent trajectories and model capabilities for code generation and debugging requests. Prompt models to complete complex coding tasks and review the accuracy of generated responses. Label, proofread, and improve machine-written and human-written software engineering-related outputs. Report quality and performance trends related to model/agent behavio

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! The Opportunity Cohere seeks a Chief Information Security Officer who can help shape Cohere’s security strategy & the broader conversation around securing AI at scale. You know how to build trust across organizations and communicate trade-offs clearly in environments where speed, innovation, and security must coexist. You will build the playbook and lead the evolution of Cohere’s global security program across corporate systems, cloud infrastructure, AI development, and enterprise operations. As a visible leader for Cohere’s security vision internally and externally you will navigate risk, represent Cohere in industry discussions, and reinforcing our commitment to building AI responsibly. In this role you will: Define and Scale Cohere’s Security Strategy: Define and execute Cohere’s overarching information security strategy in alignment with business priorities and long-term company growth. Build a Modern Risk, Governance & Compliance Program: Lead Cohere in identifying, assessing, and mitigating security risk across all business functions. Secure AI Systems and Technical Infrastructure: Lead the security architecture st

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? To have the opportunity to collaborate with Cohere researchers and tools on designing and implementing novel research ideas and shipping state-of-the-art models to production. We have openings in teams covering base model training, retrieval augmented generation, data and evaluation, safety, and finetuning, to name a few; and we are open to receiving intern applications in any research area relating to LLMs to broaden your research connections while obtaining deep experience in a growing AI startup. Please Note: To be eligible for a Research Internship, you must be currently pursuing a PhD in Machine Learning, NLP, or a related discipline. You need to be available for a full-time internship that lasts for 4-6 months. As a Cohere Research Intern, you will: Conduct cutting-edge machine learning research, building and training large language models. Focus on research projects aimed at expanding the frontier of knowledge in language modelling and associate areas such as evaluation, multimodal models, optimisation etc. Disseminate your research results through the production of publications, datasets, and code. Contrib

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 Growth Products team drives rider and driver acquisition to scale the business and balance the marketplace. We specialize in incentive and messaging targeting, budget optimization, and paid media measurement, and move rapidly to test new ideas and products. As a Data Scientist expert in causal inference and marketing mix models (MMM), you will lead our efforts to measure and optimize investments across marketing channels. Responsibilities: Deliver results across the entire lifecycle of data science solutions for Growth: from defining the problem with cross-functional stakeholders to deploying production models that address key business problems. Own complex domains and develop long-term roadmaps to maximize business impact. Build statistical pipelines, write production code, and design/analyze experiments. Participate in the science on-call rotation to ensure automated campaigns operate successfully. Experience: Advanced degree in statistics, economics, mathematics, or equivalent industry experience. 4+ years of industry experience in causal inference or data science. Proven ability to apply statistics to unstructured problems and deliver measurable results. Deep technical expertise in causal inference and tackling challenging measurement problems. Expertise in marketing mix modeling is highly preferred. Expertise in SQL and experience with large-scale data platforms. Proficiency in Python and working within production coding environments. Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled Mental health benefits Family building benefits Child care and pet benefits 401(k) plan with company match to help save for your future In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team membe

About the Role: Tubi's content platform is the engine behind one of the largest free streaming services in the world. Every play, every deal, every creator, every frame of video flows through systems CPE owns, and the surface area is enormous. Distributed services running on the hottest path of Tubi's traffic. Video pipelines processing one of the largest workloads in streaming. Workflow engines automating the operations that used to consume entire teams. Creator-facing products turning a back-office process into a real platform. And on top of all of it, an AI-native rebuild of the CMS that most companies aren't willing to attempt. This isn't a single-domain role. It's a platform where backend, frontend, video, infrastructure, and applied AI all collide at the scale where decisions actually matter, where an architectural choice ripples across millions of titles and billions of requests, and where the difference between "good enough" and "great" shows up in revenue. We're looking for builders who want to range across domains — backend one quarter, frontend the next, applied AI the one after that — and who want their work to be felt: by viewers when a title plays instantly, by creators when they go live the same day, by Content Ops when a workflow runs itself, and by the business when the platform stops being a cost center and starts being a force multiplier. The infrastructure is already there. The mandate is already there. What's missing is the people who want to build the thing, not talk about it. Come build it. This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office two days/week. What You'll Do: You'll work on systems that sit at the heart of Tubi's business, where the content pipeline meets the viewer, the creator, and increasingly, the AI agent. The work spans the full stack of a modern content platform: distributed services, video infrastructure, workflow automation, and applied AI, all running at

Toradex is a global company strongly focused on engineering & technology. We’re powered by a diverse & uniquely gifted workforce. We pursue the best people to propel our innovative vision of embedded computing and IoT. If you’re interested in being a driving force at an agile technology company, engineering clever computing solutions & helping other companies bring their products to life, we should talk. About the Role We are looking for a motivated Electronics Assembly Operator to support circuits assembly, soldering, rework, repair, inspection, and testing activities. This role is ideal for someone who is detail-oriented, hands-on, and comfortable following work instructions, IPC standards, and quality requirements in an electronics manufacturing environment. Key Responsibilities · Assemble, install, replace, and repair electronic components and connectors on PCBAs according to drawings, work instructions, IPC standards, and quality requirements · Perform hand soldering, touch-up, and component-level rework for through-hole, surface-mount, and fine-pitch components · Complete approved PCBA rework and repair, including solder bridge removal, lifted lead correction, connector replacement, and related defect corrections · Operate selective soldering and depaneling equipment while maintaining yield, quality, and basic autonomous maintenance requirements · Assist in materials handling and station setups · Inspect PCBAs for solder quality, component placement, polarity, cleanliness, and workmanship against IPC and internal standards · Document defects, corrective actions, inspection results, and traceability information for rework and repair activities · Support box build, final assembly, troubleshooting, repair verification, and continuous improvement activities across Production, Testing, Quality, and Engineering · Maintain a clean, organized, ESD-safe workstation and follow company procedures, SOPs, ISO requirements, and safety practices Skill

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

About Scale AI At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI) and building upon our prior model evaluation work with enterprise customers and governments to deepen our capabilities and offerings for public and private evaluations. About Data Engine Our Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data we produce is some of the most critical work for how humanity will interact with AI. About Our FDE Team Generating high-quality data is the core problem our business solves. We aim to make producing and delivering high-quality data seamless and efficient for operators and customers. Our Team is building customer and operator-specific infrastructure to provide high-quality data with low turnaround time. You'll be exposed to the cutting edge of the Generative AI industry while directly interfacing with the leading model-building organizations in the space, including the top AI research labs and government agencies. Join us in shaping the future of Artificial General Intelligence. As a Forward Deployed Engineer, you'll be at the forefront of providing the critical data infrastructure that powers the most advanced AI models, directly influencing how humanity interacts with AI. You will work with the world’s leading AI companies and government agencies to solve their most complex AI data-related problems. Responsibilities: Drive Impact: Directly contribute to the advancement of AI by delivering critical data solutions for leading AI innovators and

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 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

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. At Tenstorrent, we're building cutting-edge AI compute solutions. Developing diagnostics programs to validate the functionality and stress the performance of our solutions is a critical part of delivering exceptional products. We are looking for Engineers to join our Diagnostics Development team. These engineers will work closely with our firmware, software, board, ASIC design and verification teams to ensure that the ASICs, boards, and AI compute systems meet the highest standards of quality and performance. This role is hybrid, based out of Toronto, Canada. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are You're curious, hands-on, and excited by the challenge of building powerful systems that sit at the intersection of hardware and software. You enjoy working close to the metal, whether that’s writing code, debugging hardware, or exploring how systems perform under stress. You thrive in collaborative environments and love learning from teammates across disciplines like firmware, ASIC design, and manufacturing. You’re motivated by impact and want to contribute to technology that’s shaping the future of AI and computing. What We Need A

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. Interns work side-by-side with top engineers in the industry while having autonomy from the get-go. They contribute to user-facing products and are able to see their work go live quickly. Lyft fosters a collaborative environment in the office, so there's always a sharp mind eager to hear about your next idea. So what's yours? Responsibilities: Own your project, while checking in with other team members throughout the day with questions and updates You leave the code in a better state than when you found it (progressive refactor) You value reliability, ensured by testing (unit, integration and load tests) Participate in code reviews to ensure code quality and distribute knowledge Continuous integration and deployment Go home knowing that your work today is meaningfully improving the lives of every Lyft driver and every Lyft passenger! Experience: Currently pursuing a Bachelor's or Master's degree in Computer Science from a university in Canada (required) , with a graduation date between December 2027 and Summer 2028 (required). For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience Available during Summer 2027 for the internship in Montreal Strong knowledge of CS fundamentals Excellent communication skills Passion for community, sustainability, and/or transportation Ability to thrive in a startup environment Contributions to open source projects Experience working with databases Experience solving real-time technology problems Experience with mobile development Must be fluent in spoken and written English and have a working proficiency in French Benefits: Mental health benefits In addition to holidays, interns receive 2 days paid time off and 3 days sick time off Subsidi

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Interns work side-by-side with top engineers in the industry while having autonomy from the get-go. They contribute to user-facing products and are able to see their work go live quickly. Lyft fosters a collaborative environment in the office, so there's always a sharp mind eager to hear about your next idea. So what's yours? Responsibilities: Own your project, while checking in with other team members throughout the day with questions and updates You leave the code in a better state than when you found it (progressive refactor) You value reliability, ensured by testing (unit, integration and load tests) Participate in code reviews to ensure code quality and distribute knowledge Continuous integration and deployment Go home knowing that your work today is meaningfully improving the lives of every Lyft driver and every Lyft passenger! Experience: Currently pursuing a Bachelor's or Master's degree in Computer Science from a university in Canada (required) , with a graduation date between December 2027 and Summer 2028 (required). For any candidates who are master's students who worked between their bachelor's and master's programs: candidates should also have less than 2 years of relevant full-time work experience Available during Summer 2027 for the internship in Toronto Strong knowledge of CS fundamentals Excellent communication skills Passion for community, sustainability, and/or transportation Ability to thrive in a startup environment Experience with real-time technology problems Contributions to open source projects Experience working with databases Experience solving real-time technology problems Experience with mobile development Benefits: Mental health benefits In addition to holidays, interns receive 2 days paid time off and 3 days sick time off Subsidized commuter benefits and Lyft ride credi