Jobs in Canada

Ai Deployment Manager in Toronto

363 active opportunities · Updated October 2026

Explore current ai deployment manager jobs in Toronto. Filter by work mode, employment type, experience, department, date posted and distance.

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

From C$146K/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. 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

AWSLinuxRestMachine Learning
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📍 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! About the Role We're looking for an Engineering Manager to lead our Deployment Engineering team in North America. This isn't a typical management role - we need someone who thrives in a fast-paced, high-growth environment and leads from the front: technically sharp, hands-on, and relentlessly focused on impact. You'll manage a team of Forward Deployed Engineers on the front lines of building agentic solutions with Cohere's North platform, balancing technical excellence with the kind of team leadership that actually moves things forward. You'll be solving complex problems and securely integrating AI into critical sectors such as finance, healthcare, and telecommunications. What You'll Do Lead and mentor a team of Forward Deployed Engineers focused on building agentic solutions with North in on-premises environments. Take ownership of customer success from technical implementation through delivery. Collaborate closely with Product, Engineering, and Sales to shape how we deliver AI to enterprises. Build relationships with technical stakeholders on the customer end. Foster a culture of continuous improvement and innovation, focusing

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📍 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! Role Overview We are seeking a Platform Experience and Developer PM to own how developers and enterprise technical teams build on, integrate with, and operate Cohere's model platform. This is a high-leverage role sitting at the intersection of three domains: Managed Services and Models as a Service. Own Cohere's managed service offerings as a product. This is broader than model serving alone. It includes the full range of how enterprises consume and operate Cohere's capabilities, from shared multi-tenant model access to dedicated single-tenant deployments, and from synchronous real-time inference to high-volume asynchronous workloads. You will own the product thinking around deployment models, data residency and regional compliance requirements, self-serve provisioning, and the operational controls that give enterprises confidence in running production workloads on Cohere’s infrastructure. API and SDK. Own the roadmap for how developers build on Cohere. This means setting the direction for our APIs and SDKs, thinking carefully about interface design and ergonomics, and ensuring we ship developer primitives that are stable, well-

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📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$108K/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. 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

Machine LearningAIGoRust
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📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$118.8K/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. Machine Learning is at the heart of Lyft’s products and decision-making. Machine Learning Engineers at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges, from pricing and marketplace frameworks that ensure reliability and competitiveness, to agentic AI platforms that automate analytical workflows, to behavioral detection systems that protect the integrity of our network. We operate at the intersection of applied ML and real business impact, shipping models that directly influence revenue, rider experience, and partner trust. Lyft Business builds products that help organizations move the people who matter most—employees, customers, patients, and guests—easily and efficiently. Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools. These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs. We're looking for a Machine Learning Engineer to design, build, and deploy ML systems across Lyft Business. This is a high-scope role: you won't be siloed into one problem area. Instead, you'll move across pricing algorithms, fraud and behavior detection, agentic AI systems, and emerging ML applications as the business evolves. You'll write production-quality code, own models end-to-end from prototyping through deployment, and collaborate closely with Data Scientists, Product Managers, and Software Engineers to translate complex business problems into scalable ML solutions. This role is ideal for someone who is technically versatile, energized by variety, and wants to see th

AWSMachine LearningAIGo
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📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$45/hr

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 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

PythonSQLMachine LearningAI
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📍 Toronto, Ontario, Canada· Full-time
✓ Quality checkedCompany trend -85.7%

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 team The Apps & Experiences Platform team is powering systems and services for all our user facing apps including Snowsight , Snowflake Intelligence , and new mobile apps . Our mission is to craft innovative backend services, features, tools, infrastructure, and AI tooling that bring such products to life with delightful user experiences. As part of our team, you'll dive into a mix of building & managing platform infrastructure, and building AI self-serve tools to support the platform and its developer’s needs. We're passionate about building a platform that is highly reliable, available, maintainable, and scalable. We are a high growth AI data cloud company and we are looking for exceptional talent like you to help build and grow our infrastructure to scale us to the next level. AS TECHNICAL LEAD & MANAGER FOR APPS & EXPERIENCES STORAGE TEAM, YOU WILL: Own the storage team’s technical strategy and execution , driving projects from initial idea formulation and detailed system design to high-quality implementation and successful deployment. Provide deep technical oversight by actively participating in design reviews, architecture discussions, and drilling into complex system implementations to ensure reliability and scalability. Serve as a key techn

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

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 Director of Machine Learning Engineering and Infrastructure to lead a hybrid team bridging advanced ML engineering with world-class infrastructure design. In this role, you will own the strategic direction and execution for scaling our machine learning capabilities while ensuring our distributed systems and infrastructure can support innovation at massive scale. You will combine technical depth with leadership excellence to guide teams that deliver both foundational ML systems and high-performance distributed services. This is a hybrid role for our Toronto office. What You'll Do: Lead and manage high-performing teams across ML engineering and ML infrastructure, fostering a culture of innovation, collaboration, and growth. Define and execute the strategic roadmap for ML systems, including recommendation, personalization, and ads optimization. Oversee the design, development, and deployment of scalable ML pipelines: data ingestion, feature engineering, model training, evaluation, and serving. Architect distributed systems to support ML workloads at scale, ensuring reliability, observability, and operational excellence. Partner closely with Product, Engineering, and Content teams to align on business goals and deliver impactful ML-driven experiences. Support best practices in experimentation, evaluation, and ML system monitoring. Ensure cost efficiency, scalability, and performance in ML infrastructure investments. Your Background: 10+ years of industry experience spanning machine learning engineering and distributed systems. 3+ years of leadership and management experience, with a proven ability to build and lead strong t

AWSMachine LearningAIGo
F
📍 Toronto, Canada· Full-time
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

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

RestAIGoExcel
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
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📍 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 building next-generation CPU and AI silicon. You’ll work at the forefront of hardware innovation, diagnosing complex issues across chips, systems, firmware, and software while collaborating with some of the brightest engineers in the industry. This role offers the opportunity to solve challenging technical problems, build impactful debug solutions, and directly influence the reliability and performance of cutting-edge AI compute platforms. This role is hybrid, based out of Toronto, Canada. 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 Experienced in hardware debug and post-silicon bring-up for CPU, SoC, or ASIC systems. Strong understanding of processor architecture and microarchitecture (RISC-V, x86, or ARM) with familiarity in debug and trace methodologies (e.g., iJTAG). Hands-on engineer who excels at diagnosing complex hardware, firmware, and software issues through root-cause analysis. Comfortable working in the lab with a passion for building debug tools, automation, and scalable methodologies. Collaborative team player with experience partnering across ASIC, firmware, software, and validation teams. What We Need

PythonAWSAIExcel
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📍 Toronto, Ontario, Canada· Full-time
✓ High-confidence listing

C$135K – C$210K/yr

Quick readStrong listing-quality and freshness signals

Overview: Guidepoint seeks an experienced AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization in production

PythonReactAWSAzure
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📍 Toronto, Ontario, Canada· Full-time
✓ High-confidence listing

C$135K – C$210K/yr

Quick readStrong listing-quality and freshness signals

Overview: Guidepoint seeks an experienced Data/AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The Senior AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization

PythonReactAWSAzure
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📍 Toronto, Canada· Full-time
✓ High-confidence listingCompany trend -72.4%

From C$40/hr

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. 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

AIGoExcelHR
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📍 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. We are seeking a hands-on Data Center Technician, IT Contractor to support the installation, deployment, relocation, cabling, inventory, maintenance, and decommissioning of servers, network equipment, storage systems, and other IT infrastructure. The successful candidate will follow established procedures, maintain accurate documentation, and coordinate effectively with internal technical teams and data center personnel. This role will be a 6-month contract fully on-site, based out of the downtown Toronto, ON Beanfield data center, with travel to Tenstorrent office locations and other data center facilities as required. 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 You bring approximately 2 to 5 years of hands-on experience in data center operations, IT infrastructure, server or network hardware, or a similar technical role. You are comfortable working with servers, network equipment, storage systems, racks, rack layouts, and copper and fiber optic cabling. You are detail-oriented, organized, and able to follow documented procedures, cabling standards, installation instructions, and safety requirements. You communicate clearly, work well wi

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