Top Machine Learning Jobs in Toronto

Develop and scale machine learning training systems for robotics data, optimize training pipelines, and collaborate with ML researchers to enhance autonomy models.

Design and develop scalable, high-performance data and API infrastructure for real-time processing. Mentor engineers and collaborate with teams to enhance AI model evaluations.

Responsible for designing experiments to evaluate AI models, developing evaluation methodologies, analyzing performance data, and collaborating on production insights.

The Senior Principal Researcher will lead AI research initiatives, mentor teams, translate research into scalable systems, and represent Huawei in the global AI community.

Develop and commercialize firmware for neural network processing on ARM-based processors. Design embedded software for real-time processing, manage buffer interrupts, and optimize compilers.

The CTO will lead Fathom's technical strategy, focusing on AI governance, building partnerships, defining standards, and advancing AI safety practices.

Build and deploy NLP and generative AI solutions using transformer-based and other ML models. Develop LLM-based features, preprocess complex unstructured data, collaborate with engineering, product, and MLOps teams, and iterate in an agile, cross-functional environment to improve customer workflows and efficiencies.

Use legal training to create and evaluate AI training data and relevance evaluations. Perform legal research and analysis, provide actionable feedback, support senior team members, present to stakeholders, and advocate for Responsible AI.

The Technical Product Manager will lead product direction, interface with engineering teams, and ensure the successful deployment of AI-powered safety systems. Responsibilities include defining product vision, translating customer needs, and maintaining high product quality.

The Co-op Researcher will research and develop cutting-edge technology in machine learning and computer vision, focusing on algorithm optimization for mobile devices.

As a Co-op Researcher, you will engage in research and development in computer vision and machine learning, optimizing algorithms and models for mobile computing constraints.

In this role, the researcher will specialize in computer vision and machine learning, developing algorithms, evaluating solutions, and collaborating with teams.

Assist in research and development of computer vision and machine learning technologies through deep learning and image analysis. Optimize algorithms for mobile deployment and contribute to projects involving image and video analysis.

The role involves leading AI/ML technical planning, evaluating new technologies, collaborating with stakeholders, and fostering innovation in the team.

As an AI/ML Engineer, you'll develop and optimize machine learning models for mobile applications, collaborate with teams, and integrate AI-driven features to enhance user experience.

The AI/ML Engineer will design, develop, and optimize machine learning models for mobile applications, collaborating with teams to enhance user experiences and innovate in AI-driven solutions.

The role involves developing infrastructure for benchmarking AI inference performance, analyzing system behavior, designing telemetry systems, and collaborating with teams to improve feature performance.

Manage and grow a small ML/GenAI engineering team while remaining hands-on: design and implement GenAI systems (agents, RAG, tool use), build NLP solutions (NER, classification, retrieval, summarization), partner with PMs and engineers to scope and ship features, and coach engineers on technical and career growth.

The role involves building standardized training frameworks, profiling model performance, collaborating with teams, and improving related tooling.

Lead design and production of next-generation search and personalization systems using LLMs, dense vector retrieval, GNNs, multi-stage ranking, and reinforcement learning. Drive GPU-based deployment (e.g., Triton), ensure <100ms latency, mentor applied scientists and MLEs, and partner cross-functionally to productionize scalable, reliable search and recommendation experiences.

Provide embedded legal counsel to product and engineering on privacy, IP, and consumer protection; lead Arena's global privacy program (GDPR, CCPA/CPRA, cross-border transfers); advise on AI governance and responsible deployment; support commercial contracts and data flow frameworks; build privacy processes, playbooks, internal agents, and legal-tech integrations to scale operations.

As a Machine Learning Engineer, you will develop scalable ML systems, work with large datasets, and collaborate with a talented AI team.

Architect and deploy scalable machine learning and generative AI systems, including LLM, RAG, inference, evaluation, and LLMOps pipelines. Develop prompting, retrieval workflows, guardrails, schema validation, and production evaluation systems focused on accuracy, safety, reliability, and cost. Lead technical decisions, collaborate with product and engineering teams, drive greenfield initiatives, and mentor engineers building secure AI-powered experiences.

As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.

As a Senior Machine Learning Engineer, you'll design and develop AI systems, focusing on LLMs and improving agent performance while mentoring engineers.