Product And Privacy Counsel in Toronto

About ElevenLabs ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $11B - multiples of 11, always. We have expanded from voice into three main platforms: ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. How we work High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you. AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. Excellence everywhere: Everything we do should match the quality of our AI models. Global team: We prioritize your talent, not your location. What we offer Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible. Growth paths: Joining ElevenLabs means joining a

About ElevenLabs ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $11B - multiples of 11, always. We have expanded from voice into three main platforms: ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. How we work High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you. AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. Excellence everywhere: Everything we do should match the quality of our AI models. Global team: We prioritize your talent, not your location. What we offer Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible. Growth paths: Joining ElevenLabs means joining a

About the Role: The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding and ads optimization that shape the future of streaming. We are seeking a highly skilled Senior Machine Learning Engineer to contribute to transformative projects in video personalization. In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy. As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross-functional teams to develop and optimize machine learning-driven solutions. This is a hybrid role in our Toronto office. What You'll Do: Design, develop, and implement recommendation systems and algorithms for a global audience Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences. Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement Your Background: 3+ years of industry experience building production Machine Learning systems BS, MSc, or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks Proficiency in building and deploying full-stack machine learning pipelines: data e

About the Role: The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding and ads optimization that shape the future of streaming. We are seeking a highly skilled Staff Machine Learning Engineer to contribute to transformative projects in video personalization. In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy. As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross-functional teams to develop and optimize machine learning-driven solutions. This is a hybrid role in our Toronto office. What You'll Do: Lead the design, development, and implementation of advanced recommendation systems and algorithms for a global audience Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences. Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement Your Background: 8+ years of industry experience building production Machine Learning systems MSc or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks Proficiency in building and deploying full-stack machine le

About the Role: As a Staff Software Engineer on the ML Infrastructure team, you will collaborate closely with the Machine Learning and Product teams to build world-class machine learning inference platforms. These platforms power essential services like personalized recommendations, search, and content understanding across Tubi. A core responsibility of this team is developing and maintaining low-latency ML model serving systems that support Deep Learning, LLM, and Search models. This involves building self-service infrastructure and critical components such as the inference engine, feature store, vector store, and experimentation engine. You will improve the way we deploy and operate our services and even contribute to open-source projects. This role grants the architectural freedom to explore new frameworks, lead critical cross-functional projects, and transform the capabilities of our ML and Product teams. Responsibilities: Design and build scalable, high throughput, and low latency distributed systems using Scala Build reusable components and services that serve various ML applications like Personalization, Search, Ads and Exploration Partner closely with ML engineers to understand their challenges and limitations and develop scalable solutions to address them. Proactively recommend solutions to keep our ML Inference stack state of the art. Take a data driven approach to identifying & optimizing latency, cost, and efficiency of our infra. Lead large scale cross functional refactorings if necessary Mentor other engineers on the team on system design, effective incident management, interviewing, leveraging LLMs for work, etc. Collaborate with ML, Product, and cross functional engineering teams to define the long term vision and architecture for ML Infrastructure at Tubi. Your Background: Experience designing and building scalable, distributed systems in any modern backend language (e.g., Scala, Java, Python, Go, C++); experience with Scala or JVM b

Level Up Your Career with Zynga! At Zynga, we bring people together through the power of play. As a global leader in interactive entertainment and a proud label of Take-Two Interactive, our games have been downloaded over 6 billion times—connecting players in 175+ countries through fun, strategy, and a little friendly competition. From thrilling casino spins to epic strategy battles, mind-bending puzzles, and social word challenges, our diverse game portfolio has something for everyone. Fan-favorites and latest hits include FarmVille™, Words With Friends™, Zynga Poker™, Game of Thrones Slots Casino™, Wizard of Oz Slots™, Hit it Rich! Slots™, Wonka Slots™, Top Eleven™, Toon Blast™, Empires & Puzzles™, Merge Dragons!™, CSR Racing™, Harry Potter: Puzzles & Spells™, Match Factory™, and Color Block Jam™—plus many more! Founded in 2007 and headquartered in California, our teams span North America, Europe, and Asia, working together to craft unforgettable gaming experiences. Whether you're spinning, strategizing, matching, or competing, Zynga is where fun meets innovation—and where you can take your career to the next level. Join us and be part of the play! Position Overview: The Senior Director, Data Platform will lead Zynga's centralized data platform and product strategy, managing one of the largest data footprints in the gaming industry—billions of daily gameplay events flowing through a cloud-native stack spanning real-time ingestion, a petabyte-scale warehouse, experimentation, and a self-serve metrics and AI platform. Operating with high autonomy and direct executive sponsorship, you will act as a pathfinder: empowering our global studios to extract maximum value from central data and transforming the group to an AI-first way of working. This highly visible role is based in Toronto and partners closely with studio leaders, central teams, and executives across Zynga's global labels. Relocation support is available. What You'll Do: Craft data product strategy:

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About The Role The Security Team is responsible for securing all things Sentry: our customers, our code, and everything in between. We are a small but growing team with broad scope, high trust, and the autonomy to tackle hard security problems with creativity and an engineering mindset. We work at a company with a strong developer culture, building a product that millions of developers genuinely love and rely on. That context shapes everything about how we operate. We take a pragmatic approach to preventing and responding to security risks. In this role not only will you build and contribute to systems which detect malicious activity, you will have the unique opportunity to implement new controls to prevent future incidents. You will work across detection and response and corporate security domains. You'll contribute to practices that keep Sentry secure as we grow: alert triage for corporate and production, detection engineering, deploying preventative controls, identity and access management, investigations and incident response, and more. You'll partner with teams across the company to prevent and respond to security incidents. You will work as a technical collaborator who prioritizes preventative controls, defense in depth, and high signal alerting practices. As Sentry expands our agentic product capabilities and development practices, you'll also find yourself at the frontier of a new set of security approaches and challenges. In this role, you will Maintain, improve, and own detection engineering systems. We own and operate our own detection stack and are building agentic triage with thoughtful security response and orc

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

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role: Sentry is expanding our Technical Customer Success team to support our growing customer base and drive deeper adoption of the Sentry Platform worldwide. As a Technical Customer Success Manager (TCSM), you’ll be a Sentry product expert responsible for ensuring customers are successfully onboarded, achieve maximum value from our platform, and uncover new opportunities for growth through additional use cases and products. You’ll play a key role in helping customers realize measurable outcomes with Sentry. In this highly cross-functional role, you’ll collaborate closely with Account Executives (AEs), Sales Engineers (SEs), and Engineering teams to ensure customers’ technical and business goals are met. This role requires strong technical expertise and a deep understanding of the Software Development Life Cycle (SDLC) and related technologies. If you’re a technologist with experience supporting technical products in customer-facing roles—and you’re eager to join a fast-growing team delivering real value through an exceptional product—we’d love to meet you. In this role you will: Become a Sentry product expert and support customers by understanding their needs and helping them achieve their goals using the Sentry Platform. Drive customer success and health through effective onboarding, adoption, value realization, and retention. Collaborate with customer key stakeholders to define business and technical objectives, and work with the customer team to achieve them. Act as a trusted, strategic advisor to each assigned customer—driving best practices, innovation, and long-term success. Partner closely with the sales te

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. Content Systems is the heart of Lyft's language ecosystem. The team is made up of two distinct disciplines, Content Design and Learning Experience Design, who create and own language across Lyft's in-app experiences that help customers succeed on the Lyft platform. We're looking for a Content Systems intern to join our team for the summer. This role will both help design and build our internal content system (think information architecture), and embed in a rotation of design teams as a content design/learning design partner in building products across the Lyft community. Of course, you won’t be alone. You'll work with designers, researchers, marketers, and product managers day in and day out to develop experiences that reach and resonate with riders. This internship will take place in our Toronto office during Summer 2027 . What we're looking for Responsibilities: Support our content system by establishing and translating information architecture to help manage content across Lyft Help teams reconsider existing systems and processes (eg publishing workflows) to align to the new information architecture Support product strategy and vision through content, working on projects as a content designer and learning experience designer Translate complicated concepts into clear in-product copy (UI, notifications, errors, and more) and learning materials Collaborate with designers, visual content creators, researchers, engineers, marketers, data science, product managers, and other stakeholders across tech and ops The ability to translate concepts across the UI, learning center, and knowledge base into connected content objects Manage multiple projects and competing priorities Maintain, evolve and champion the Lyft brand voice and style Skills: Excellent writing skills; ability to

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft is seeking a qualitative User Experience Research Intern to join our team, which aspires to elevate the user experience for our drivers and riders across 300+ cities nationwide. You will conduct research studies, as well as participate in studies alongside more senior researchers from which you’ll gain strong mentorship. You will partner with Design, Product Management, Analytics, and Engineering in order to derive deep insights about our users’ behaviors and attitudes, and communicate results and actionable recommendations across the company. Interns contribute to user-facing products, working side-by-side with top User Experience Research team members in the industry while having autonomy from the get-go. 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: Design and conduct studies across key Lyft product areas -- independently and in conjunction with more senior researchers. You will utilize methods such as ethnographic & field research, diary studies, surveys, user/usability testing (remote and in-person), guerrilla research, and any other methods you find impactful Review, analyze, and communicate qualitative and/or quantitative data to generate tactical and strategic insights, as well as actionable recommendations which drive product innovation and design improvements for users Experience: Currently pursuing a Master's or PhD degree in Human-Computer Interaction, Anthropology, Design, Psychology, Cognitive Science, or a related field from a university in Canada with a graduation date between December 2027 and Summer 2028 (required) Available during Summer 2027 for an internship in Toronto Extraordinary organizational skills and meticulous eye for detail Str

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. As a Senior Software Engineer, Data on the Mapping team, you will collaborate with our world-class team of engineers, product managers, and scientists to grow and improve the quality of recommended routes and accuracy of our travel time estimations. You will lead the architecture and long-term technical direction of our offline experimentation tooling and route simulation services — the systems that let Lyft test routing changes safely before they reach production. You'll also build scalable data pipelines for experimentation, analytics, and machine learning models, along with the data governance and observability systems that keep them trustworthy. Your work will enable integration with partner teams and allow stakeholders across Engineering, Data Science, and Product to make data-informed decisions that directly impact Lyft’s growth and profitability. Our technology stack is based on the latest technologies such as AWS, Databricks, Kubernetes and Airflow. You will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on projects that directly impact millions of riders and drivers. Responsibilities Own core data pipelines end-to-end, building deep subject matter expertise in the systems you manage and defining/managing SLAs for pipelines, services, and datasets to ensure reliability at scale Serve as the technical owner and architectural lead for our offline experimentation platform and route simulation services, setting technical direction, evaluating trade-offs, and ensuring the systems scale with Lyft's routing and mapping ambitions Continuously evolve data models and schemas to meet business and engineering requirements Develop AI tools that support self-service management of data pipelines (ETL) and schema evolution, and perform han

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