Top Machine Learning Jobs in Toronto

The Researcher will design AI systems for scientific algorithm discovery, collaborate with teams, publish findings, and drive innovative research.

As an Intern Researcher, contribute to research on large language model-based agents, focusing on evaluation and autonomous reasoning. Involves formulating problems, conducting experiments, and contributing to publishable work.

Lead technical vision, research, and engineering for a unified computer vision platform. Define long-term research agenda, drive MLOps and deployment across edge/cloud, set performance metrics, manage and scale distributed teams, and translate product needs into scalable, production-ready visual intelligence solutions.

Lead a product portfolio for Clio's core case management experience, utilizing legal expertise to drive innovation and user adoption while simplifying attorney workflows with AI tools.

The AI Product Manager will lead the development of AI-powered applications, collaborating with engineers and designers to align AI technologies with user needs and business objectives.

As an AI Product Manager, you will lead the product development for AI-driven features, collaborating with engineers and designers to optimize user experiences and ensure alignment with business objectives.

Lead and execute IT audits, assess IT risk and compliance (e.g., PCI DSS, PIPEDA), advise business and IT on controls, develop audit plans, report findings to senior management, and help integrate AI into audit practices while managing and mentoring the audit team.

Design, develop, and maintain scalable full-stack features for SOTI XSight using C#, .NET, TypeScript, and Angular. Drive architecture, integrate analytics/AI, mentor developers, troubleshoot complex issues, and collaborate with stakeholders to deliver high-quality, cloud-ready solutions.

The Associate Director of Data Sciences drives SOTI's AI and data strategy, develops AI capabilities, and mentors teams to enhance product efficiencies.

Lead and develop a credit risk analyst team while owning underwriting, exposure decisions, portfolio monitoring, loss forecasting, reporting, and provisioning. Partner with Data Science, Risk Analytics, Finance, Product, and Support to build credit risk models, policies, controls, and automated workflows. Establish an AI-native credit risk practice for payments and future lending products, communicate portfolio trends to leadership, and support vendor evaluations and product launches.

Lead product strategy, portfolio execution, and AI-first transformation for Colliers’ proprietary commercial technology platforms. Oversee multiple Product Management teams, establish roadmaps and FED governance, partner with Data, AI, Engineering, and global business leaders, and deliver enterprise B2B products for sales and services professionals. Drive adoption, product telemetry, KPIs, ROI measurement, and AI-enabled workflows using cloud and analytics technologies.

As a Research Machine Learning Scientist, you will develop and apply deep learning techniques on large-scale datasets while collaborating with engineers. You will also research and innovate in AI applications to improve banking services.

Contribute to designing, training, testing, and deploying machine learning models and production pipelines. Collaborate with product managers, data scientists, and ML engineers to solve business problems, analyze data, communicate findings, and participate in code and specification reviews. The intern will apply research papers in working code, build efficient ML workflows, and develop high-quality software in a collaborative environment.

Own a scoped project in machine learning, AI infrastructure, MLOps, data, robotics, simulation, or world models. Work with production repositories, clusters, and data to deliver a lasting artifact such as a dataset, benchmark, evaluation, or tool, supported by a mentor and technical write-up.

Leads software engineering teams and owns technical delivery across XR/MR applications, motion-capture pipelines, embedded systems, and cloud SaaS products. Responsibilities include people management, architecture, design reviews, code quality, SDLC delivery, DevOps, AI-assisted development tooling, process improvement, executive reporting, and client-facing technical support. The role requires strong software engineering fundamentals, production architecture ownership, leadership experience, LLM and machine learning knowledge, and hands-on AI tool integration.

Develop experimental AI techniques for agentic marketing applications, especially image and video generation. Build proofs of concept, autonomous evaluation and improvement systems, realistic AI-generated video, and brand-aligned creative generation workflows. The role requires strong quantitative and probabilistic thinking, backend architecture skills, creativity with LLM applications, and product intuition.

Develop and prototype robotic hardware for expressive, interactive consumer robots. Design mechanical systems, electronics, PCBs and embedded integrations, collaborate with ML/software engineers, and iterate on perception and interaction hardware for production-ready robots.

Senior Product Designer on Enterprise Experience Design team creating end-to-end enterprise/B2B tools for content planning, production, launch, and promotion. Lead user research, prototyping, visual and interaction design, usability testing, and cross-functional collaboration with PMs, engineers, data scientists, and stakeholders. Drive product strategy, design systems, and scalable solutions for global users while working PST hours and traveling quarterly to company offices.

Staff Machine Learning Engineer sets technical direction for production ML architecture, deployment, serving, monitoring, testing, CI/CD, observability, and incident response. The role builds high-throughput, low-latency ML services; leads MLOps practices; supports recommendations, ranking, multimodal systems, LLMs, and AI agents; and drives cross-team technical decisions and multi-quarter initiatives.

Design, build, deploy, and optimize production-grade AI systems, including LLM applications, autonomous agents, multi-agent workflows, machine-learning models, data and inference pipelines, and evaluation frameworks. Develop secure, scalable AI services using retrieval-augmented generation, tool calling, orchestration, and model fine-tuning. Monitor reliability, performance, safety, cost, and business outcomes while applying governance, observability, and responsible AI practices.

Develop AI/ML strategy and production software for Smile Digital Health’s healthcare data platform. Design architectures and implement semantic matching, RAG, document parsing, agentic systems, knowledge graphs, and evaluation workflows. Write clean, tested, documented code, integrate external components, conduct reviews, collaborate with clients and product teams, contribute to technical strategy, and mentor developers in an Agile environment.

Build and support machine learning pipelines and services across cloud and on-premise environments. Deploy, monitor, optimize, version, and retrain models using MLOps practices. Collaborate with ML engineers, data scientists, and product teams while working with AWS, Snowflake, data processing tools, and Linux systems. Contribute to scalable workflows, data privacy and compliance, code reviews, and knowledge sharing.

Conduct advanced AI research in LLMs, agentic AI, reinforcement learning, knowledge graphs, generative AI, and responsible AI. Develop, evaluate, deploy, and maintain machine learning solutions, publish research, and productize findings for financial applications. Collaborate with scientists, engineers, product managers, and business stakeholders to identify opportunities, translate requirements into analytical approaches, and deliver innovative solutions that improve client experiences and business decision-making.

Lead end-to-end product design for real-time insights, reporting, and analytics in a legal SaaS product. Translate complex data and domain logic into scalable, accessible UI patterns, prototype AI-powered features, conduct customer research, and partner with product and engineering to drive strategy, launches, and iterative improvements.

Lead the strategy, design, deployment, and scale-up of AI-powered health products across the Global South. Own product roadmaps, execution, government-system integration, stakeholder adoption, partnerships, grant development, and portfolio expansion. Collaborate with engineering, machine learning, program, and domain teams to deliver sustainable, measurable public-health impact.