Quality Assurance Specialist in Canada

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Engineering Opportunity Reporting to the Director of Quality & Performance, this role as Engineering Manager of Performance & Resilience will drive performance and resiliency improvements for the Auth0 product at Okta. Here you'll be working with some of the most advanced technology in the space, helping to streamline and secure billions of access requests a year. In this role, you will work closely with architects, platform team members, and product engineers to build the testing infrastructure that keeps Auth0 performant at scale — including the frameworks, tooling, and realistic datasets that make that testing meaningful. The ideal candidate is passionate about software quality and architecture, a self-starter, intellectually curious, and brings deep experience with performance testing, load testing frameworks, dataset generation, performance analysis, monitoring tooling, and chaos engineering. What you’ll be doing Collaborate with architects, tech lead, product owners, security and operations engineers to implement best practices related to performance and resiliency Communicate and organize cross-team projects with high business

You will: Source and acquire quality candidates for high volume positions to meet hiring and activation goals Review applications and screen candidates Support candidates throughout the recruiting process Partner with other growth recruiters, ops leads and cross-functional leaders to understand Scale’s business needs, then devise and execute on the recruiting strategy needed to deliver on them. Follow and manage processes that will evolve over time as the company grows. Represent and champion the brand, promoting its value proposition to candidates and driving engagement. Represent Scale at occasional onsite growth recruiting events. Ideally you have: 2+ years of recruiting/sourcing experience in a fast-paced, high-growth environment. Excellent written and verbal communication skills, with the ability to tailor messaging to diverse audiences Experience sourcing candidates and filling high volume roles Experience acting as the primary candidate liaison, delivering white-glove service through timely updates and personalized support throughout the interview process Nice to have: Previous experience in a start-up. Either experience managing a full-cycle recruiting experience, or a passion and ability to learn to do so. Experience with various tools such as Linkedin Recruiter, Clay, Modernloop, Gem Extreme attention to detail AI builder, AI-forward operator, or strong interest in agentic coding and experimenting with AI tooling The hourly salary range for this position is $40 to $55/hr. This is a remote position with occasional travels required for onsite growth recruiting events. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allow

Scale works with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling). This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities. In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models. You will: Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities. Design and experiment new approaches to preference optimization. Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning. Excellent written and verbal communication skills Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals Previous experience in a customer facing role. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined du

Scale works with the industry's leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) and evaluation. This role is on the evaluation pod within the GenAI Research Organization and will focus on building benchmarks and diagnosing model failure modes in both text and multimodal modalities. In this role, you will develop rigorous evaluations and diagnostic methods that reveal where frontier models fail and why. You will collaborate with researchers and engineers to define best practices in evaluation-driven AI development. You will also partner with top foundation model labs to translate failure analysis into technical and strategic input on the next generation of generative AI models. You will: Analyze model behavior to identify, characterize, and diagnose failure modes in frontier LLMs and Agents. You’ll identify everything from capability gaps and reasoning errors to robustness and alignment issues, all focusing on RCA. Design and build benchmarks and evaluation methods that measure LLM capabilities in both text and multimodal modalities. Apply post-training expertise (SFT, RLHF, reward modeling) to connect observed failures to the data and training interventions that address them. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning, and with LLM evaluation or benchmark development. Excellent written and verbal communication skills. Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals. Previous experience in a customer facing r

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview Instacart’s Catalog Operations team powers the data that makes shopping effortless. Catalog data represents the vast majority of what customers see when they browse, search, and buy. Our quality, coverage, and accuracy directly shape the customer experience. We are an AI-first operations team that builds LLM-driven pipelines and scalable quality programs to create, enrich, and govern product data across the Instacart ecosystem. We’re looking for a Catalog Operations Analyst II to accelerate our Health and Meals pillar within Online Grocery, one of our top strategic priorities. In this role, you will drive end-to-end data quality and enrichment for health, nutrition, and meal-related attributes, partnering closely with Catalog Engineering, Data Science, Product, and ML, as well as external data providers and BPOs. You’ll join a tight-knit team of 8 who roll

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit’s Ads Data Science team is looking for a Senior Staff Data Scientist to lead the scientific strategy behind Reddit’s ads measurement and signal systems. This role sits at the center of how Reddit proves advertiser value, improves signal quality, builds privacy-aware measurement systems, and connects ads exposure to real advertiser outcomes. As a Senior Staff Data Scientist for Ads Measurement, you will be the principal architect of our technical vision and the driving force behind the next generation of our measurement ecosystem. In a landscape rapidly shifting due to privacy regulations, browser changes, and evolving platform dynamics, you will spearhead innovation across experimental design (incrementality/lift), identity, signals, and privacy-safe 1P/3P measurement. This is a high-visibility, high-impact role requiring a rare blend of deep experimentation & causal inference expertise, strategic foresight, and the ability to influence cross-functional executives and industry standards. You will not just adapt to the changing ad-tech environment, you will redefine how we measure value. Responsibilities Technical Vision & Strategy: Define the long-term data science vision & strategy across ads measurement, signal quality, identity, attribution, and privacy. Establish how Reddit should evaluate advertiser value, measurement quality, and signal utility across first-party and third-party products. Set the Cross-Pillar Measurement Science Strategy: Define the long-term data science strategy across a

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. Scale Frontier Data is the organization behind the training and evaluation data that frontier labs depend on. We build the systems, tooling, and expert workflows that turn hard human expertise into signals that models can learn from, across reasoning, coding, agentic tool use, and domain expertise. About our Customer Platform team: Our Customer Platform Team plays a pivotal role in integrating our platform with external systems and ensuring seamless, reliable connectivity for both internal users and customers. As the leader of this team, you’ll drive the strategy, architecture, and development of our connectivity solutions, focusing on API integration, distributed systems, and a robust data platform. Your role will be crucial in maintaining and enhancing our platform’s ability to meet the needs of both our internal and external stakeholders. Responsibilities: Own large areas within our product Comfortable working cross functionally, whether that be internal or external customers Build features end-to-end: front-end, back-end, system design, debugging and testing Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Influence the culture, values, and processes of a growing engineering team Inspire and mentor less experienced engineers Collaborating with cross-functional teams to define, design, and ship new product features and experiences. Requirements: At least 7-10 years of relevant experience is preferred Track record of shipping high-quality products and features at scale Desire to work in a very fast-paced environment Abil

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! In September 2026 we raised a $350 million Series E at a $3.5 billion valuation , and we are scaling our engineering and research teams to meet demand. The role Frontier AI data is expensive to make and hard to measure. Every task we deliver is tested against the strongest models, often through many long-running agent rollouts. Your job is to make that process faster, cheaper, and more rigorous with ML and AI You will be one of the early members of ML & Research Engineering at Snorkel. You will study how frontier-grade data is generated and evaluated, form hypotheses, validate them against real production data, and ship the winners at scale. You will shape the discipline's direction, its standards, and the team that grows around it. What you'll work on Efficient agentic evals. Cut the cost of long-horizon agent evaluation with adaptive sampling, statistically grounded early stopping, model cascades, caching, and cheap-first gating. AI model routing. Route every eval and judge call to the cheapest model that clears the quality bar, with fallback, monitoring, and cost attribution. Fine-tuned small models. Fine-tune and serve open-weight models (LoRA and other

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

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. For 10 years, Scale has provided the high-quality data and full-stack technologies that power the world's leading models, and has helped enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. Public Sector engineers build the core product including the systems required to ingest and process federal datasets that support real-time decision-making in contested environments. As a New Grad Software Engineer on this team, you will own meaningful, mission-facing work from day one: shipping features, sitting with the government stakeholders who use them, and iterating fast. Example Projects Build multi-layered guardrails that keep agents safe and predictable in high-stakes federal environments Optimize data retrieval for agents, including RAG pipelines over large, heterogeneous federal datasets Build orchestration for fleets of asynchronous agents running long-horizon tasks Develop systems that automatically alert users to deviations and anomalies in incoming data Create interfaces that illustrate how an agent reached a decision, so operators can audit and trust its output Develop data pipelines and ML infrastructure that make previously siloed government data sources accessible to agents Build evaluation infrastructure that measures model reliability against mission requirements Ship full-stack tooling that lets analysts query, visualize, and explore mission data Deploy and harden applications into secure, air-gapped, and cloud-native government environments Requirements A graduation date in Fall 2026 or Spring 2027 with a Bachelor's degree (or equivalent) in a relevant field (Computer Science, EECS, Computer Engineering, Statistics) Product engineering expe

Here at Appian, our values of Intensity and Excellence define who we are. We set high standards and live up to them, ensuring that everything we do is done with care and quality. We approach every challenge with ambition and commitment, holding ourselves and each other accountable to achieve the best results. When you join Appian, you’ll be part of a passionate team dedicated to accomplishing hard things, together. About the Team Appian Customer Success is obsessed with delivering exceptional customer outcomes and high-velocity business impact. Our Public Sector team acts as a trusted strategic partner to government agencies and organizations, bringing their most vital ideas to life. By joining this high-performing team, you will strengthen and evolve your technical consulting skills while accelerating the adoption of our AI-Powered Process Automation platform across critical public infrastructure. As a Senior Consultant, you will step into a pivotal leadership role at the intersection of public sector strategy and modern technical innovation. This is your opportunity to move beyond isolated coding tasks and own the end-to-end delivery of highly visible, complex enterprise systems. You will lead small engineering teams, architect robust integrations, and serve as a trusted technical advisor to client stakeholders - enabling enterprise organizations to achieve true Enterprise-Grade Orchestration . What You’ll Do Lead Project Delivery: Oversee and drive the entire project lifecycle to define, design, and implement custom automation solutions using the Appian platform. Mentor & Develop Talent: Actively lead, coach, and mentor junior consultants through fast-paced software implementations, fostering a culture of technical excellence. Architect Integrations: Build seamless data pipelines and robust APIs to integrate multiple external enterprise systems using REST, SOAP, and JDBC connections. Drive Data Modeling: Design and launch sophisticated relational data

Here at Appian, our values of Intensity and Excellence define who we are. We set high standards and live up to them, ensuring that everything we do is done with care and quality. We approach every challenge with ambition and commitment, holding ourselves and each other accountable to achieve the best results. When you join Appian, you’ll be part of a passionate team dedicated to accomplishing hard things, together. Appian Customer Success is obsessed with delivering exceptional customer outcomes and driving mission-critical business impact. Grounded in our core values of Excellence and Intensity, we act as elite technical advisors to our commercial clients. By joining this high-performance team, you will champion a culture of candid communication and excellence while accelerating global adoption of our AI-Powered Process Automation platform. As a Principal Consultant, you will occupy a leadership position at the intersection of enterprise business strategy and complex technical delivery. This role matters now more than ever because you won't just execute projects - you will define the client experience and how they are delivered. You will partner directly with Appian Architects and Technical Delivery Managers, lead large-scale consulting initiatives, and serve as a vital mentor to the next generation of engineers, ensuring our clients achieve world-class Enterprise-Grade Orchestration. What You’ll Do Lead Enterprise Delivery: Command the entire project lifecycle to define, design, and implement custom automation solutions using the Appian platform for major commercial clients. Direct High-Performing Teams: Lead and mentor consultants through fast-paced software implementations, instilling a dedication to going "beyond completion." Partner with Leadership: Collaborate directly with Appian Architects and Technical Delivery Managers to design resilient, scalable, and secure system architectures. Architect Complex Integrations: Build secure, high-throughput APIs

Here at Appian, our values of Intensity and Excellence define who we are. We set high standards and live up to them, ensuring that everything we do is done with care and quality. We approach every challenge with ambition and commitment, holding ourselves and each other accountable to achieve the best results. When you join Appian, you’ll be part of a passionate team dedicated to accomplishing hard things, together. Are you looking to combine your passion for technology with your penchant for strategic problem solving? Appian Customer success is obsessed with great customer outcomes. We deliver mission-critical business impact fast, and are directly responsible for partnering with our customers to bring their best ideas to life. Joining the Customer Success team will provide you with the support and growth you need to strengthen and evolve your skills within the consulting field. Technical Delivery Managers (TDMs) are responsible for two of our most important company objectives: (1) ensure our customers achieve remarkable business results through technology engagements and (2) drive customer growth through technology expertise, trusted advice, relationships, and, most importantly, demonstrated results. TDMs manage and deliver innovative solutions built on the Appian platform for our customers, overseeing all aspects of agile delivery for Appian led engagements, including risk management and impediment removal. TDMs also team closely with front-line sales reps to drive growth in strategic accounts and integrated deals. TDMs engage in all aspects of driving results and growth at strategic accounts, including: project management, account management, relationship building (both customers and partners), financial management, opportunity qualification, problem identification, project/use case definition, demand generation, services positioning, and account strategy. All of these activities are performed in partnership with Appian Sales, Appian Partners, and oth

About Scale Scale’s mission is to develop reliable AI systems for the world’s most important decisions. As the leading AI data foundry, we provide the high-quality data and full-stack technologies that power the world’s most advanced models — fueling breakthroughs in generative AI, defense, and autonomous vehicles. We partner with leading enterprises and governments to bring AI into production that performs when it matters most, combining rigorous evaluation with full-stack deployment so our customers can build AI they can trust. About the Team Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams — agent evaluation and oversight, orchestration and tool-use infrastructure, model and systems optimization, and applied research on new agent capabilities — and this role is not scoped to any single one of them. We’re growing fast, with increasing traction across both commercial and public sector customers, and we’re just getting started — this team will define what dependable, production-grade agentic AI looks like. About the Role As a Staff Machine Learning Research Engineer, you will operate across the full breadth of AIS’s technical needs — wherever the hardest ML problem in agentic AI happens to be that quarter. This could mean training and fine-tuning models, designing evaluation and observability systems, building improvement loops from production data, prototyping novel agent architectures, or designing internal systems and tooling that boost productivity across teams. You’re not tied to one team’s roadmap; you’re expected to move to where the technical leverage is highest, and t

About Scale AI At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. Scale Frontier Data is the organization behind the training and evaluation data that frontier labs depend on. We build the systems, tooling, and expert workflows that turn hard human expertise into signals that models can learn from, across reasoning, coding, agentic tool use, and domain expertise. Reinforcement learning environments are now the center of gravity for that work: the difference between a model that demos well and a model that reliably completes long-horizon work is almost always the quality of the environments and reward signals it was trained against. Responsibilities As a Staff Software Engineer, RL Environments, you'll own the technical foundation for how Scale builds, runs, verifies, and delivers RL environments at scale. An RL environment is a real piece of software: a containerized world with real dependencies, real state, real tools, and a grader that has to be correct even when the agent is creative about breaking it. Building one is a full-stack engineering problem. Building thousands of them reproducibly, cheaply, with trustworthy reward signals and throughput measured in millions of rollouts is a systems problem that very few people have solved. You'll work on both. You'll design the platform: sandboxed execution, environment packaging and versioning, rollout orchestration, trajectory capture, verifier frameworks, and the authoring surfaces that let engineers and domain experts produce environments without reinventing infrastructure each time. And you'll go deep on the environments themselves by instrumenting real applications, designing task suites that expose specific capability gaps, and building graders that