Deployment Lead 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. As a Data Scientist on the Mapping team, you will collaborate with our world class team of scientists, engineers, product managers, and designers to grow and improve the quality of recommended routes and accuracy of our travel time estimations. We're looking for a passionate, driven Data Scientist who is excited to dive into our geospatial, behavioural and mobility data, and build a best-in-class mapping product that provides safe, efficient, and seamless navigation for our rideshare drivers. Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our mapping products and make business decisions that put our customers first. The Mapping team serves models and systems that determine the most efficient routes, fastest travel estimates and process real-time map data signals to detect traffic, closures and slowdowns. Working with our business and analytics partners, the team owns tools to ensure Lyft offers routes that our users trust. This will involve identifying and scoping opportunities, recommending technical solutions, designing experiments, and measuring the impact of new features. You will help us solve some of the most impactful problems in Mapping, including: How do we accurately predict acute and chronic traffic conditions? How do we improve the recommendations of our routing algorithms? How do we keep our travel estimation promises to our riders and drivers? How do we benchmark and measure the success of our services? Responsibilities: Own the complete lifecycle of algorithmic solutions from problem formulation, data exploration, and feature engineering to deployment, monitoring, and iteration Prioritize and lead deep dives into our data to uncover new product and business opportunities Partner closely with E

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. Okta enables universal, secure access to technology for every user and organization. The Device Identity and Access team ensures that every endpoint interacting with corporate resources is trusted, healthy, and secure. Our pillar spans four domains: Device Identity, Device Authentication, Device Security Posture, and Endpoint AI Security. We are hiring a Senior Product Manager to drive our Zero Trust Authentication group. In this role, you will lead the core execution, performance, and deployment strategy for Okta’s foundational endpoint products. You will own the operational excellence of Okta Verify , FastPass , and Device Assurance , ensuring that our core passwordless authentication flows and device posture engines remain performant, secure, and incredibly easy for global enterprises to deploy at scale. This is a critical, high-impact role designed for a highly autonomous product manager. You will take on the tactical execution and smaller strategic investments for our endpoint authenticators, acting as the team's operational anchor so that our senior product leaders can continuously expand our strategic frontiers. What you will own You will bridge user experience and deep systems engineering to ensure our core authentication products scale reliably for millions of global users. Core Device Assurance Execution: Own the roadmap for our baseline security posture checks (such as OS version validation, disk encryption, and firewall status). You will m

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 a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically eva

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About the role The App Runtime team is building a platform that lets every Snowflake user go from an idea to a live, deployed web application (Node.js first) in minutes. We own the end-to-end experience of building and running apps, from Cortex AI-assisted development to deployment in a secure, scalable infrastructure. Apps built on the platform inherit Snowflake's security, governance, lineage, and access controls by default. See Deploy Faster with Snowflake Apps . As a Staff/Principal Engineer, you will shape the product and its architecture. It’s a high leverage role - you will lead a team to scale and harden an early-stage, public-preview product. Your decisions will have a long-lasting impact on the future of Snowflake as an app platform. This role requires a unique combination of deep hands-on expertise in scalability, performance and security, great product instincts, customer obsession and the organizational influence to drive cross-team programs. Responsibilities Own the roadmap and technical decisions to evolve the public-preview platform into a production-grade one, adding features like horizontal scaling, cost efficiency via suspend/resume, support for stacks beyond Node.js, and stronger access and data-governance controls Stay deeply hands-on by authoring specs

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. As a Datacenter Liquid Cooling Architect, you will define, design, and architect next-generation liquid cooling infrastructure for Tenstorrent’s large-scale AI training and inference clusters. You will partner with systems engineering, mechanical engineering, software, and cross-functional design teams to develop chassis-, rack-, and cluster-scale cooling solutions, including CDU integration, telemetry and control, leak detection, and resilient operating strategies. This role will help shape reliable AI datacenter architectures and deployments for both internal and external customers. This role is on-site, based out of Toronto, Canada, Austin, Texas or Santa Clara, California. 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 A datacenter and system thermal design professional with 10+ years of experience architecting cooling infrastructure for complex computing environments. An experienced liquid cooling architect who can design chassis- and rack-scale solutions for large AI training and inference clusters. A systems thinker who understands how mechanical, electrical, software, facility, and systems engineering decisions come toge

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? Are you energized by building high-performance, scalable and reliable machine learning systems? Do you want to help define and build the next generation of AI platforms powering advanced NLP applications? We are looking for a Site Reliability Engineer to join the Model Serving team at Cohere. The team is responsible for developing, deploying, and operating the AI platform delivering Cohere's large language models through easy to use API endpoints. In this role, you will work closely with many teams to deploy optimized NLP models to production in low latency, high throughput, and high availability environments. You will also get the opportunity to interface with customers and create customized deployments to meet their specific needs. As a Site Reliability Engineer you will: Build self-service systems that automate managing, deploying and operating services. This includes our custom Kubernetes operators that support language model deployments. Automate environment observability and resilience. Enable all developers to troubleshoot and resolve problems. Take steps required to ensure we hit defined SLOs, including pa

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! Security Clearance: Active Secret+ clearance strongly preferred; candidates eligible and willing to obtain clearance will also be considered. More information about Canadian Security Clearance is available here . As an Infrastructure Security Engineer, your key responsibilities include: Deploy, and manage infrastructure for Protected B classified environments, ensuring compliance with ITSG-33 and Canadian government standards Design and implement security controls for cloud (AWS, GCP, Azure) and hybrid/multi-cloud deployments Evaluate, implement, and manage security tools and technologies for training cluster and inference infrastructure hardening Implement security best practices including IAM, encryption, logging, and monitoring Participate in security incident response activities, including detection, analysis, containment, and remediation Conduct regular vulnerability assessments and penetration testing of infrastructure components Maintain comprehensive security documentation, procedures, and configurations for classified environments Maintain active Secret+ security clearance and adhere to all Canadian government security

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! Director, SPM Implementation About the Team The Customer Operations team partners with new and existing customers to implement and optimize the company’s platform, ensuring clients maximize the revenue-driving potential of their sales compensation programs. The team leads complex implementations, drives operational excellence, and continuously evolves Sales Performance Management (SPM) processes through data-driven insights and scalable platform solutions. As a Director of Implementation , you will lead the strategic direction of implementation and customer onboarding across a portfolio of enterprise customers. You will oversee implementation teams, guide architectural design of customer solutions, and collaborate closely with Product, Engineering, and Revenue teams to ensure the platform evolves in alignment with customer needs and business priorities. If you’re passionate about building high-performing teams, driving customer impact through data and technology, and shaping the future of sales operations , we’d love to hear from you. What You'll Be Doing Leadership & Strategy Define and lead the implementation strategy and operational framework for onboarding and scaling customer deployments. Build, mentor, and lead a high-performing implementation team , establishing best practices, processes, and standards for delivery excellence. Partner with executive leadership to align customer implementation strategy with company growth and product roadmap priorities . Establish KPI

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 autonomous transition is a transformational opportunity for Lyft. Our strategy focuses on becoming the preferred marketplace, fleet, and operational partner for the world's best Autonomous Vehicle (AV) providers. As AV deployments scale across new markets, the operational infrastructure that enables safe, compliant, and high-quality service becomes a critical competitive advantage. This role sits at the heart of that infrastructure - owning the systems, processes, and partner alignment that allow Lyft to operate at the standards our AV partners require and our riders expect. As a qualified candidate, you have a track record of building and running complex operational programs in highly regulated or standards-driven environments. You are energized by cross-functional complexity - comfortable leading structured implementation processes that span many teams while keeping a clear eye on compliance and quality outcomes. You bring a program management mindset, strong stakeholder communication skills, and the judgment to navigate ambiguity in a fast-moving industry. Responsibilities: Own execution of AV partner audits end-to-end. That includes evidence collection, submission, partner and third-party review, mitigation oversight, and closeout, across concurrent certification cycles for multiple markets and AV partners, domestic and international. Act as a strategic leader within the company to support cross-functional teams’ compliance controls and readiness for partner scrutiny Drive coordination across teams including EHS, Legal, Safety, HR, IT and Operations for every deliverable. Translate partner and regulatory requirements into concrete, assignable asks and ensure deadlines are met Maintain and continuously improve the audit tracking system, including the evidence library, audit trail, and submissi

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

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 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, Data Science or related major 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 an internship in Toronto Strong knowledge of CS fundamentals Knowledge of SQL and data modeling fundamentals Experience working with databases Excellent communication skills Interest in solving large scale data problems in a real world scenario Passion for community, sustainability, and/or transportation 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 credits Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft belie

About the Role: We're hiring Senior and Staff Data Platform Engineers to join the Data Infrastructure teams in Toronto. Together these teams own the infrastructure that processes billions of events per day: Spark-on-Kubernetes, Flink and Kinesis pipelines, a multi-petabyte Delta Lake, a large-scale MemoryDB feature store, Databricks multi-environment operations, and the catalog and lifecycle systems that govern it. The team is small and senior. Each engineer owns major platform components: you design it, build it, and support it in production. 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: Spark-on-Kubernetes — EKS-based compute platform for Spark workloads: cluster configuration, Pod Identity IAM, job environment setup, Kustomize overlays, and shadow canary validation Event ingestion — Rust services and Flink jobs processing billions of events per day over Kinesis; throughput, reliability, on-call response, and AI-assisted operational tooling to reduce toil Platform infrastructure — Terraform modules for environment provisioning, cross-account AWS IAM, ARC runner infrastructure, and CI/CD for data platform changes Feature store and ML compute — Flink-based real-time feature pipelines feeding a large-scale MemoryDB cluster; GPU capacity governance and Databricks multi-environment operations for ML training workloads Workflow orchestration and CDC — Airflow-based DAG deployment, change data capture pipeline operations, and data quality monitoring Your Background: 3+ years building and operating production data platform infrastructure at the cluster or platform level, across Spark, Flink, Kinesis, Kubernetes, or equivalent Deep experience in at least one of: Spark-on-K8s cluster operations, Rust-based data or systems engineering, Kubernetes platform engineering and IaC, or data catalog and governance tooling Production AWS experience or equivalent: EKS, S3, Kinesis, and mu

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

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

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. We are looking for experienced backend software engineers to join our claims tech engineering team. Our vision is to tangibly reduce risk on the Lyft platform, and by extension reduce insurance cost. Our team is dedicated to centralizing the entire claims operation onto a unified risk platform. This consolidation of data, workflows, and communications aims to foster proactive measures, enhance efficiency, ensure consistency, and provide valuable insights. These efforts are designed to effectively reduce claims costs as Lyft's operations expand. Additionally, our team is responsible for maintaining robust relationships with our third-party insurance partners, guaranteeing timely, proactive, and precise sharing of claim data. Responsibilities: Write well-crafted, well-tested, readable, maintainable code Own feature from product spec to successful high quality development, deployment and maintenance Participate in code reviews to ensure code quality and distribute knowledge Respond to external questions and requests. Unblock, support and communicate with stakeholders to achieve results Experience: 3+ years of relevant professional experience Experience with object-oriented programming Experience in distributed systems Experience working with databases, relational or NoSQL Write clear, scalable and clear design documentation Design, build and improve a set of team owned components Benefits: Extended health and dental coverage options, along with life insurance and disability benefits Mental health benefits Family building benefits Child care and pet benefits Access to a Lyft funded Health Care Savings Account RRSP plan with company match to help save for your future In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows