Jobs in Canada

Ai Systems Engineer in Canada

1,268 active opportunities · Updated October 2026

Explore current ai systems engineer jobs across Canada. Filter by work mode, employment type, experience, department, date posted and distance.

SA
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $264.8K/yr

Quick readStrong listing-quality and freshness signals

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. About the General Agents Team The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers. About the Role As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments. You will: Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases. Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints. Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings. Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs. Productionize frontier agent techniques (e.g.,

PythonAWSRestMachine Learning
SA
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $252K/yr

Quick readStrong listing-quality and freshness signals

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

TypeScriptPythonReactAWS
SA
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $216K/yr

Quick readStrong listing-quality and freshness signals

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

AWSRestAIGo
SA
📍 San Francisco, Canada
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

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

TypeScriptPythonReactMongoDB
SA
📍 San Francisco, Canada· Full-time
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

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. Scale's internship is not a side project. Interns own real, shipped work on the same roadmaps as full-time engineers, with mentorship from world-class talent and a culture that values ownership, speed, and truth-seeking. Many of our interns return as full-time Scaliens. Example Projects Build reinforcement learning and post-training data pipelines that power frontier model development Develop evaluation infrastructure that measures model reliability for enterprise and public sector customers Ship agentic AI applications and the tooling that makes them observable, testable, and safe to deploy Ship tools that accelerate the growth of new qualified contributors on Scale's platform Build fraud-detection systems that remove bad actors and keep Scale's contributor base safe and trusted Use models to estimate the quality of tasks and contributors, and guarantee quality on requests at large scale Devise advanced matching algorithms that pair contributors to customers for optimal turnaround and accuracy Create optimized and efficient UI/UX tooling, in combination with ML algorithms, for 100k+ contributors completing billions of complex tasks Develop new AI infrastructure products to visualize, query, and explore Scale data Requirements A graduation date in Fall 2027 or Spring 2028 with a Bachelor's degree (or equivalent) in a relevant field (Computer Science, EECS, Computer Engineering, Statistics) Available for a Summer 2027 internship (May/June start dates) in San Franci

TypeScriptPythonReactMongoDB
SA
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $252K/yr

Quick readStrong listing-quality and freshness signals

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineeri

PythonAWSAzureGCP
SA
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $288K/yr

Quick readStrong listing-quality and freshness signals

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Senior Staff Frontier Agents Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineering & Optimization Create sophisticate

PythonAWSAzureGCP
T
📍 Toronto, Ontario, Canada· Full-time
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

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. Tenstorrent is seeking a skilled Software Engineer with a passion for building high-performance, low-level systems software. In this role, you’ll contribute to the development and optimization of the infrastructure that powers our cutting-edge processors, with a primary focus on C/C++ development and low-level programming. You'll work closely with large inference and training model development to further drive Scale Out software and hardware performance. This role is hybrid, based out of Toronto, ON. Who You Are Strong C or C++ systems engineer with a deep understanding of memory, threading, I/O, and low-level execution models. Experienced building low-level software, drivers, embedded systems, or performance-critical infrastructure. Comfortable working close to hardware and curious about how systems behave under the hood. Proficient with Linux systems programming and debugging tools such as gdb, strace, and perf. Structured problem solver who thrives in fast-paced, highly technical environments. What We Need Design, develop, and maintain core infrastructure software that interfaces directly with Tenstorrent hardware. Build low-level libraries and APIs for communication and synchronization across compute nodes. Optimize system-level software for performance, scalability, and reliability in distributed environments. Support hardware

AWSLinuxAIC++
C
📍 Toronto, Ontario, Canada· Full-time
✓ Quality checkedCompany trend -91.5%

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

AWSAzureGCPKubernetes
L
📍 Montreal, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$88K/yr

Quick readStrong listing-quality and freshness signals

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 Bikes & Scooters team is developing the future of micro-mobility and we are looking for a Mechanical Engineer to come in and help drive the development of our newest vehicles and sustain our fleet in operation. Responsibilities: Drive design decision by collaborating with product, engineering (EE/ME/FW/SW), reliability, and systems engineering teams Lead post-launch sustaining activities intended to support a smooth transition into production while maintaining high quality standards Derive technical architecture and engineering specifications from product requirements Use analysis to support engineering designs Lead sustaining and continuous improvement projects from concept through release and into field operations Work with GSM and Manufacturing teams to vet supply chain and production partners Prototype; create quick experimental mock-ups and meticulous mechanical models Research technologies and scope development opportunities Develop CAD databases and drawing packages, and drive handoff to manufacturers Support the build and test product development cycle, travel required Test failure analysis and solution validation to complete successful product development Conduct field failure analysis and solution evaluation Lead large projects from idea to positive execution Act on feedback to learn and grow Effectively communicate across cross functional teams to achieve results Experience: BS or MS degree in Mechanical Engineering or related technical field, and 5+ years of related industry experience Experience leading the development of a feature or module of a consumer product Strong foundation in mechanical engineering fundamentals, including solid mechanics, electromagnetics, thermodynamics, and knowledge of basic engineering materials and manufacturing processes Experience in perfo

AISupply ChainHR
O
📍 Toronto, Ontario, Canada· Full-time
✓ High-confidence listingCompany trend -63.6%

From C$110K/yr

Quick readStrong listing-quality and freshness signals

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. We are looking for a Software Engineer II to join the Auth0 Security Engineering organization. You'll help build and maintain the security guardrails for our multi-cloud environment, implementing security and compliance standards as programmatic, code-driven policies. What You Will Do Cloud Security Controls: Implement and maintain organization-wide controls (SCPs, Azure Policy) balancing protection with developer experience. Identity & Access Management (IAM): Build and update templates and permission boundaries that govern how services and humans interact with our cloud, applying the principle of least privilege. Infrastructure & Network Security: Contribute to the security standards for VPC architecture, edge networking, and cross-account connectivity. System Design: Help build systems and processes that validate the security posture of the platform, enforcing our security policies and surfacing actionable feedback for engineering teams. Growth & Collaboration: Partner with teammates across the organization, share what you learn, and continually deepen your security expertise. What You Bring Cloud & Infrastructure Experience: 3+ years of experience in software engineering or information security, with hands-on exposure to cloud-native environments, Kubernetes (EKS, AKS), and cloud security concepts. Policy & Automation: Experience building or maintaining automated controls and infrastructure-as-code, ideally within Terraform workflows

JavaScriptPythonJavaAWS
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📍 Toronto, Ontario, Canada· Full-time· Remote
✓ High-confidence listingCompany trend -91.5%

From £215K/yr

Quick readStrong listing-quality and freshness signals

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? North is Cohere's cutting-edge AI workspace platform, designed to transform how enterprises leverage AI. It provides a secure, customizable environment that enables organizations to deploy AI solutions while maintaining strict control over sensitive data. The North app is deployed directly to customers in highly regulated industries, delivering a seamless experience that empowers teams to work efficiently and securely at their best. We're seeking iOS and Android experts to join our close-knit team, where you'll drive exceptional impact on mission-critical projects. As a Senior Mobile Engineer, you will: Build and ship features for North, our AI workspace platform Collaborate with UI/UX designers to implement interface elements As security and privacy are paramount, you will sometimes need to re-invent the wheel, and won’t be able to use the most popular libraries or tooling Collaborate with researchers to productionize state-of-the-art models and techniques Research new technologies and best practices You may be a good fit if you: Have shipped (lots of) Android and iOS code (Kotlin, Swift) in production Built nati

GitAIKotlinSwift
C
📍 Canada· Contract
✓ Quality checkedCompany trend -91.5%

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? This role will focus on breaking down engineering tasks such as reporting, component search and handling of material billing/information into individual steps that can be tackled through tool use. Your breakdown will teach the Cohere model the logic needed to complete each task. Please Note: This is a part-time independent contractor position available within Canada . We seek candidates who are able to commit to 16 hours per week minimum at a 30 CAD/hour contract rate. This role is BYOD 💻 - Bring Your Own Device (laptop). Remote work within Canada. 12 month contract. Performance incentives included! As a Data Annotation Specialist, you will: Evaluate the model's ability to respond to engineering procedures and workflows Task models to complete engineering tasks along with verified information to evaluate the accuracy of the model's responses Label, proofread, and improve machine-written and human-written engineering-related outputs. Follow our style guide, and make recommendations on unique situations that fall outside of its scope. You may be a good fit if you have: 3+ years of industry experience working in eng

E(
📍 Vancouver, BC, Canada· Full-time
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. Who You Are We're looking for innovative and passionate Machine Learning Engineers to join our team. You are someone who loves solving complex problems, enjoys the challenges of working with huge data sets, and has a knack for turning theoretical concepts into practical, scalable solutions. You are a strong team player but also thrive in autonomous environments where your ideas can make a significant impact. You love utilizing machine learning techniques to push the boundaries of what is possible within the realm of Natural Language Processing, Information Retrieval and related spaces. Most importantly, you are excited to be part of a mission-oriented high-growth startup that can create a lasting impact. You Will Conceptualize, develop, and deploy machine learning models that underpin our NLP, retrieval, ranking, reasoning, dialog and code-generation systems. Implement advanced machine learning algorithms, such as Transformer-based models, reinforcement learning, ensemble learning, and agent-based systems to continually improve the performance of our AI systems. Process and analyze large, complex datasets (structured, semi-structured, and unstructured), and use your findings to inf

PythonSQLAzureGCP
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📍 Toronto, Canada· Hybrid
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

About the Team: Tubi's Internal Tools team is at the forefront of AI integration, developing everything from developer resources to production-grade AI for business operations. We are the group responsible for turning AI from an experiment into an operating capability: training, infrastructure, developer agents, and AI-powered business systems. Engineers operate with high ownership and autonomy, collaborating on shared architectural decisions and AI infrastructure. What You'll Do: Own systems end to end — design them, build them, and support them in production. Lead the projects you own: sequence the work, decide what lands first, and set technical direction for the engineers working with you. Sit with the people who use what you build, and turn what you learn there into a system. Design the service boundaries, contracts and schema evolution that let our platforms grow without breaking the teams depending on them. Make our AI systems dependable in production: evaluation harnesses, human approval steps before an agent acts, retries that handle a model returning something unexpected, and cost tracking that tells you what a task costs before you run it. Build what other engineers build on — agent skills, tool and MCP integrations, shared libraries — and raise the bar through code review, design discussion and mentoring. Spot the platform work nobody has asked for yet, make the case for it, and build it. Your Background: 5+ years of professional experience building and operating production systems, from design through production ownership. A system you designed and can walk us through end to end — where its boundaries sit, what constrained it, and what you chose against. Strong programming proficiency in a statically typed language such as Rust, Go, C++, Java, Kotlin, C#, or TypeScript. Production Rust is a plus rather than a requirement. You have owned a service in production: you wrote the runbooks, you knew what it cost, and you were the one paged when it broke. Expe

TypeScriptJavaAIC++
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