System Verification Co Design Engineer in Toronto

We are a global team of innovators and pioneers dedicated to shaping the future of observability. At New Relic, we build an intelligent platform that empowers companies to thrive in an AI-first world by giving them unparalleled insight into their complex systems. As we continue to expand our global footprint, we're looking for passionate people to join our mission. If you're ready to help the world's best companies optimize their digital applications, we invite you to explore a career with us! Your opportunity As the Manager, GTM Engineering (AI and Automation), you will be key to constructing and maintaining our "Revenue Velocity" engine with a specialized team of architects. In this high impact role, you will report to the Director of Enterprise Systems & Solutions. You will be responsible for the successful technical integration of advanced AI and automation tools throughout our Go-To-Market (GTM) technology stack. This role requires a proactive player-coach who balances thinking strategically about our revenue systems while remaining deeply involved in the creation of durable, data-driven automation frameworks. What you'll do GTM Tech Stack Management: Integrate with and optimize the core Sales and Marketing technology stack (Salesforce, Clay, Rox, Boomi, Salesloft) in alignment with customer-centric initiatives. Workflow & AI Automation: Execute end-to-end automated workflows (lead scoring, routing, alerts) and deploy AI/ML solutions to scale business outreach efficiency. Data Integrity & Analytics: Manage data pipelines and routine hygiene (deduplication, enrichment) across systems; maintain dashboards to track key GTM metrics and deliver forecasting to leadership. Process Execution & Enablement: Work with Program teams to map GTM workflows and drive technical projects from requirements gathering through implementation and user adoption. This role requires 2+ years of people management or relevant leadership experience, such as lead

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. About the Role We are seeking a Senior Product Manager to drive the vision, strategy, and execution for a key product area within the Auth0 Identity Security product line, with a focused mandate on the rapidly evolving domain of Agentic Security. This role sits at the intersection of product strategy, cross-functional leadership, and agile execution — requiring someone who can both shape long-term direction and deliver with precision. We are the team that builds solutions that protect our customer’s Auth0 environments. Our group delivers features such as attack protection, bot detection, adaptive MFA, identity security for AI Agents and related analytics / insights on the effectiveness of our solutions in thwarting attacks from bad actors. The ideal candidate brings direct, hands-on experience in agentic security product management, with a deep understanding of how AI agents are built, orchestrated, and secured. This includes practical knowledge of agentic workflows, MCP servers, agentic tooling, and their use through productivity applications such as Claude Code. A core focus of this role is runtime security & AI agent classification: building real-time detection, behavioral analysis, and protection capabilities for agentic systems. The successful candidate will have command of the OWASP Top 10 for Agentic AI attack vectors and mitigations, and will bring experience in identifying and responding to threats such as prompt injection, agent intent anomali

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 divide between business needs and technical delivery is one of the most persistent challenges in enterprise technology, where People teams struggle to articulate requirements and engineering teams lack the business context to build truly impactful solutions. As a Senior Business Solution Architect for People at Lyft, you'll eliminate this gap by serving as the critical connection point between our People teams and our Corporate Engineering and IT (CEIT) organization. This customer obsessed role uniquely combines deep functional business expertise with strong technical acumen, with an AI native approach, enabling you to translate complex business needs into systemized, scalable solutions while driving AI-enabled transformation across the People function. We're seeking a strategic thinker who thrives at the intersection of business and technology, possesses exceptional communication skills across both technical and non-technical audiences, and is dedicated to architecting the future AI Native state of how the People function operates. You'll be the trusted advisor to both business leaders and engineering teams, ensuring our People organization has systems and processes that scale with our business while our engineering teams build solutions that truly move the needle. With AI fundamentally reshaping how the People function gets work done, your expertise will be critical in helping us responsibly harness these technologies to drive operational excellence. In this role, you'll reimagine People workflows through an AI-first lens, design business processes that balance operational excellence with technical feasibility, and champion automation that elevates teams from tactical execution to strategic impact. If you are a candidate who has the vision of what could be, who has the ability to cultivat

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. Our core philosophy is to empower developers to self-serve rather than be bottlenecked by a central quality team. We believe that by creating smart, automated tooling, we can eliminate common roadblocks, making developers happier and more productive. The Rider Quality team is focused on elevating quality, testing, and accessibility across our mobile platforms. We are currently shifting our strategy to heavily leverage automation and AI to revolutionize how we approach testing. We're not doing traditional QA - we're building the future of quality engineering. This is a chance to step into a Senior role where you won't just write code; you'll design systems that define how hundreds of engineers deliver product faster, happier, and with fewer bugs. We are fundamentally shifting away from manual processes and existing automation frameworks that struggle to keep up, betting heavily on Artificial Intelligence and agentic frameworks to drive a massive "shift left" in our organization. Success in this role is measured by tangible impact, including increased developer satisfaction, engineering hours saved, and bugs/incidents avoided in production. We are seeking a highly skilled and innovative Senior Software Engineer to join our team. You will be instrumental in building the next generation of our quality assurance platform. You will be responsible for designing and developing advanced AI-powered tooling for test case generation, review, and execution. Your work will directly impact our ability to provide fast, actionable feedback to developers, "shifting left" to ensure quality from the earliest stages of development. You will play a key role in integrating these tools into our existing developer workflows, ensuring seamless adoption and maximum impact. We are looking for someone with a strong background in

Engineering Manager, AI Conversation Platform Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The newly formed Conversation Platform team aims to build a conversation platform for all merchants who use Stripe. We are doing so by (a) automating the easy tasks, and (b) assisting our users in the difficult tasks. Some examples include customizing the Stripe landing page to suggest bespoke integrations, allowing users to command the Stripe API in natural language, and resolving user issues automatically. We are developing RAG based systems on the latest LLMs as well as fine-tuning our own models. We’re an end-to-end team going from ideas to models to shipping in production. What you’ll do Responsibilities Driving an ambitious vision for AI/ML that benefits our users Setting the technical & process direction for the team based on business goals Brainstorm and coordinate product integrations with partner teams Proposing new ideas and building prototypes Be an integral part of a larger ML community internally & externally Hire & develop a world-class team to deliver high-quality ML systems. Coach engineers to help them grow in their careers and maintain a high bar Who you are We are looking for ML Engineering Managers who are passionate about using ML to improve products and delight customers. You have experience leading teams that develop streaming feature pipelines, build ML models, and deploy them to production, even if it involves making substantial changes to backend code. You a

Engineering Manager, AI Conversation Platform Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The newly formed Conversation Platform team aims to build a conversation platform for all merchants who use Stripe. We are doing so by (a) automating the easy tasks, and (b) assisting our users in the difficult tasks. Some examples include customizing the Stripe landing page to suggest bespoke integrations, allowing users to command the Stripe API in natural language, and resolving user issues automatically. We are developing RAG based systems on the latest LLMs as well as fine-tuning our own models. We’re an end-to-end team going from ideas to models to shipping in production. What you’ll do Responsibilities Driving an ambitious vision for AI/ML that benefits our users Setting the technical & process direction for the team based on business goals Brainstorm and coordinate product integrations with partner teams Proposing new ideas and building prototypes Be an integral part of a larger ML community internally & externally Hire & develop a world-class team to deliver high-quality ML systems. Coach engineers to help them grow in their careers and maintain a high bar Who you are We are looking for ML Engineering Managers who are passionate about using ML to improve products and delight customers. You have experience leading teams that develop streaming feature pipelines, build ML models, and deploy them to production, even if it involves making substantial changes to backend code. You a

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: Okta Access Gateway (OAG) Enterprises run on a mix of modern cloud services and mission-critical on-premises systems (such as Oracle E-Business Suite, SAP, PeopleSoft, and custom legacy web apps). Okta Access Gateway (OAG) solves the enterprise hybrid cloud challenge by extending Okta’s cloud identity, Adaptive MFA, and Zero Trust security policies to on-premises and legacy applications without requiring custom code changes or traditional VPNs. As the Engineering Manager for Okta Access Gateway in Toronto, you will lead and grow a team of software engineers building the next generation of our hybrid access and gateway infrastructure. You will partner closely with Product Management, Architecture, Security, and Quality teams to deliver high-throughput, mission-critical security software deployed across multi-cloud and enterprise datacenters globally. What You’ll Do People Leadership & Team Growth Lead, mentor, and empower an engineering team, fostering an inclusive, high-performance, and psychologically safe engineering culture. Drive career progression, goal setting, regular 1:1s, and continuous feedback to help engineers grow their technical and leadership skills. Attract, interview, and hire diverse engineering talent to scale Okta’s engineering presence in Toronto. Delivery & Operational Excellence Own the end-to-end execution and delivery of key product roadmap initiatives, balancing feature velocity, technical debt, and softwar

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 Driver team is dedicated to fostering a platform of high-quality service by empowering drivers to perform their best. We are looking for a product-minded engineer who wants to build and improve products that sit at the center of the core driver experience. Products you drive will solve pain points that matter most to drivers by streamlining key interactions, reducing friction, and creating systems that feel intuitive, fair, and supportive. As an engineer at Lyft, you'll collaborate with teams like product, data science, analytics, and operations on code that empower us to iterate quickly, while focusing on delighting our passengers and drivers. Responsibilities: Design and implement backend features end-to-end with clear ownership, delivering well-scoped work from technical design through to production with moderate guidance from senior engineers Write clean, reliable, well-tested code that meets team standards and holds up in code review Participate actively in code reviews, giving specific and constructive feedback while continuing to develop your own review instincts Debug and resolve issues across backend services including performance bottlenecks, reliability problems, and data integrity issues Collaborate with product managers, designers, and partner engineering teams to clarify requirements and surface technical constraints early Contribute to technical discussions and help evaluate implementation approaches for new features Write unit and integration tests for your own code and develop familiarity with the team's broader testing and observability practices Address technical debt and make incremental improvements to existing services as part of regular development work Participate in on-call rotations, respond to production incidents, and support teammates in mitigating custome

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: We're seeking a Director of Product Support Operations to lead the team that runs how Tubi's Tech Org plans, executes, and ships. PSO is a deliberately lean, AI-first team of Technical Program Managers and Customer Experience specialists built around three durable jobs: orchestrating agentic systems, people, and the cross-team programs that land Tubi's most complex initiatives for over 100 million monthly active users. You will own the Tech Org's most complex, company-level programs, spanning live events, platform integrations, monetization, and financial operations, along with the agentic systems that carry the org's operational load. You will also own the customer experience function end to end and run the Tech Org's operating cadences, including planning cycles, executive business reviews, and org-wide communications. You'll work closely with engineering, product, design, data science, and finance leaders as a trusted executive partner. This team consists of builders, not just coordinators. If you're passionate about building with AI rather than coordinating around it, landing complex programs at company scale, and developing world-class talent while staying hands-on yourself, this is the role for you. This is a hybrid role based out of our San Francisco, New York, Los Angeles, or Toronto offices. What You'll Do: Define the multi-year strategy and 12-month roadmap for Product Support Operations, aligning the portfolio with company objectives Lead, develop, and recruit high-performing Technical Program Management and Customer Experience team members, setting a high bar through direct feedback and rigorous performance management Operate as a player-coach: personally design, ship, and maintain agentic workflows and lead high-stakes programs while modeling the builder-TPM standard for the function Own execution of the Tech Org's most complex, company-level programs spanning multiple organizations and external partners, with impact validated by metrics

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: Tubi is seeking a highly skilled and experienced QA Automation Engineer to lead quality assurance initiatives for our cutting-edge streaming and AI-driven product features. This pivotal role involves ensuring exceptional end-to-end user experiences, robust streaming playback, and the accuracy and integrity of our AI/ML features across web, mobile, and OTT platforms. We're looking for a candidate with a strong background in streaming QA and deep technical knowledge of media workflows. You'll be instrumental in collaborating with engineering, product, and data science teams to define comprehensive QA strategies that guarantee both functional excellence and data-level quality 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: Design and lead test strategies for streaming workflows, playback systems, and AI-powered features. Test across platforms (web, mobile, and connected TV) to ensure functional parity and playback stability. Validate streaming performance—including ABR logic, encoding pipelines, and DRM integrations—under diverse real-world conditions. Debug with precision using tools like Charles Proxy, Chrome DevTools, ADB, and Xcode. Collaborate with data and ML teams to validate AI model updates, recommendations, and personalization accuracy. Leverage AI-assisted QA tools to enhance regression coverage, UI validation, and anomaly detection. Contribute to automation and CI/CD frameworks, driving faster, more reliable releases. Oversee QA deliverables for multiple concurrent releases and ensure seamless sign-off for production launches. Monitor live environments for playback or recommendation anomalies post-release and escalate issues promptly. Continuously improve QA processes, metrics, and reporting for streaming and AI validation. Your Background: Bachelor’s degree in Computer Science, Software Engineering, or related field, or equivalent hands-on experi

About the Role: Tubi is seeking a highly skilled and experienced Senior QA Automation Engineer to lead quality assurance initiatives for our cutting-edge streaming and AI-driven product features. This pivotal role involves ensuring exceptional end-to-end user experiences, robust streaming playback, and the accuracy and integrity of our AI/ML features across web, mobile, and OTT platforms. We're looking for a candidate with a strong background in streaming QA and deep technical knowledge of media workflows. You'll be instrumental in collaborating with engineering, product, and data science teams to define comprehensive QA strategies that guarantee both functional excellence and data-level quality. This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office three days/week. What You'll Do: Design and lead test strategies for streaming workflows, playback systems, and AI-powered features. Test across platforms (web, mobile, and connected TV) to ensure functional parity and playback stability. Validate streaming performance—including ABR logic, encoding pipelines, and DRM integrations—under diverse real-world conditions. Debug with precision using tools like Charles Proxy, Chrome DevTools, ADB, and Xcode. Collaborate with data and ML teams to validate AI model updates, recommendations, and personalization accuracy. Leverage AI-assisted QA tools to enhance regression coverage, UI validation, and anomaly detection. Contribute to automation and CI/CD frameworks, driving faster, more reliable releases. Help drive a shift-left testing approach by engaging early in the software development lifecycle, partnering with product managers, engineers, and data scientists to identify quality risks, define test strategies, and ensure testability during requirements and design phases. Oversee QA deliverables for multiple concurrent releases and ensure seamless sign-off for production launches. Monitor live environments for playback or reco

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 VP / Director of Machine Learning Engineering to lead and build a high-performing team while staying close to the technical work. This is a hands-on leadership role: you will set the strategic direction for our recommendation, personalization, and ads optimization systems, including recommendation foundation modeling, and you will stay in the algorithms and the code, conducting deep dives into modeling components and guiding the hardest technical decisions yourself. You will tackle complex machine learning problems at scale and partner closely with cross-functional teams to ship solutions that measurably improve how hundreds of millions of viewers experience Tubi. What You’ll Do Lead, build, and grow a high-performing ML engineering team, fostering a culture of technical excellence, ownership, and rapid iteration. Define and drive the ML strategy and long-term technical roadmap for recommendation, personalization, and ads optimization, including recommendation foundation modeling, identifying opportunities for ML to shape Tubi’s broader product and business strategy. Stay hands-on: conduct deep dives into algorithmic components and systems, ensuring models are optimized for both performance and scalability across regions and product areas. Lead the design, development, and implementation of advanced recommendation systems and algorithms, contributing directly to the most challenging technical problems. Build and deploy robust, full-stack ML pipelines: data extraction, feature development, model training, testing, deployment, and serving. Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring