Top Machine Learning Jobs in Toronto

Design and deploy machine learning systems for autonomous vehicles, collaborating with teams to improve model performance and safety using real-world data.

The Senior Staff Applied ML Engineer will lead ML modeling and data analysis, mentor teams, and integrate AI-driven features and workflows across multiple products.

Design and lead end-to-end AI/ML and GenAI architectures (data pipelines, training, inference, MLOps). Advise clients, integrate LLMs, build RAG systems, benchmark platforms, mentor teams, ensure responsible AI, and align ML strategy with business goals.

Develop and deploy ML-based perception algorithms for robotics, optimize pipelines, and collaborate across disciplines for integration.

The role involves designing and implementing machine learning systems for knowledge representation and temporal reasoning, focusing on organizational intelligence. Responsibilities include building LLM-powered pipelines, developing memory algorithms, and researching various ML techniques.

Design, develop, and deploy machine learning pipelines. Implement MLOps practices and optimize models. Collaborate on data pipelines and cloud deployment.

The role involves solving customer problems by building ML solutions, engaging with various stakeholders, and taking ownership of the outcome through deployment.

The AI/ML Engineering Manager leads ML engineering teams, manages client engagements, shapes architecture, ensures technical quality, and drives business growth through ML operations.

The role involves building production ML models for voice AI, focusing on fine-tuning, deploying, and evaluating models to enhance human-like interactions.

As a Sales Executive, you will hunt for new clients, manage enterprise accounts, and create revenue streams while collaborating with internal teams.

Design and implement machine learning algorithms for robotic manipulation, focusing on RL and IL. Collaborate across disciplines to ensure integration and successful deployment.

Lead design and deployment of production-grade AI solutions, build multi-agent systems and cloud-native ML infrastructure, apply rigorous statistical evaluation, implement generative and predictive models, champion MLOps and data pipeline best practices, and collaborate with clients to translate business needs into technical solutions.

The Senior Machine Learning Developer in Advertiser Growth will design budget pacing systems, integrate Generative AI models, build experimentation infrastructure, and ensure high-scale billing reliability at Unity's ad-tech ecosystem.

The AI Director will oversee ML bot development and implementation, identify AI opportunities, educate teams, and prototype AI solutions.