Top Python Jobs in Toronto

Design, build, and deploy agentic AI workflows, LLM-enabled services, and cloud-native platform components. Integrate AI capabilities with enterprise systems, ensure production readiness, implement guardrails, testing, and monitoring, and collaborate with architects, delivery managers, and stakeholders to deliver secure, scalable AI-enabled automation and workflow solutions.

Support the Trading Strategy desk by building and maintaining data pipelines, tools, and analytics for quantitative, thematic, and macro research. Assist development and testing of trading strategies, maintain internal technology assets, monitor markets and events, and provide support for trading processes, risk management, and collaboration with internal and external stakeholders.

Lead and scale a product-focused data science organization to build production ML systems for personalization, recommendation, experimentation, and causal inference. Define strategy, partner with Product and Engineering, own end-to-end ML lifecycle, mentor the team, and measure product impact through robust analytics and monitoring.

Join a research-focused team to integrate AI (LLMs and autonomous agents) into mobile platform development. Build AI-driven code generation and agentic systems, design core mobile components, and collaborate across teams to deploy AI-enhanced developer tooling and monitoring for HarmonyOS and large-scale mobile ecosystems.

Serve as the technical lead for Cyera's platform, driving customer onboarding, adoption, and ROI. Design custom use cases, troubleshoot issues, lead technical workshops and executive reviews, mentor team members, advocate customer feedback to product, and monitor customer health to enable expansion and retention.

Build and deploy production LLM/ML pipelines for patent workflows: retrieval, multi-step prompt pipelines, evals frameworks, fine-tuning, agentic workflows, monitoring, and cloud deployment. Collaborate with attorneys and cross-functional teams to convert domain expertise into robust, scalable inference and data solutions.

Design, build, and maintain end-to-end full‑stack features across Python/FastAPI backend, Next.js frontend, and LLM inference pipelines. Collaborate cross‑functionally to deliver scalable AI-powered patent analysis, optimize performance, address production issues, and reduce technical debt while improving engineering practices.

Perform hands-on analytics for live-service games: analyze player behavior, retention, monetization, and economy health; build and maintain dashboards; write complex SQL workflows; partner across product, live ops, finance, and engineering; run experiments and modeling; define KPIs and improve data quality; present insights and recommendations to stakeholders.

Lead cross-functional teams to define, build, and deliver production-grade AI/ML solutions. Translate business objectives into technically feasible architectures, drive roadmaps, enforce MLOps and engineering standards, ensure governance and model risk controls, and measure business value from models. Mentor colleagues and coordinate cloud-native deployment, monitoring, and lifecycle management of AI systems.

Own and maintain data platform infrastructure: provision Snowflake via Terraform, build CI/CD for dbt, implement data quality and observability, extend the OpenMetadata catalog, create developer tooling and reproducible environments, and ensure secure, production-ready data pipelines.

Lead and grow a Data Engineering team to modernize enterprise data platforms (Snowflake/Databricks), deliver secure scalable batch and real-time pipelines, enable DataOps/MLOps, establish CI/CD and IaC practices, monitor platform health, and drive strategic platform migrations and performance optimizations with cross-functional stakeholders.

Lead the development and delivery of AI-driven product capabilities, transforming data into actionable insights while mentoring a high-performing team of data scientists and engineers.

As a Research Engineer, you will develop algorithms for world models focusing on generative and predictive modeling within complex environments, optimizing model deployment, and collaborating with research teams.

As a Data Engineer, you will design and implement scalable data pipelines and solutions, collaborate with teams, and apply new technologies in an Agile environment.

Collaborate to scale self-driving systems, build training frameworks, profile model performance, and evaluate emerging technologies for training and inference.

The Data Engineer will design scalable data pipelines, manage data solutions, collaborate with teams, and ensure project delivery on time while applying new technologies.

The Cloud and DevOps Developer will provide cloud infrastructure builds, implement DevOps best practices, and participate in Agile project delivery.

As a Research Engineer, you will develop and enhance AI algorithms for self-driving vehicles, collaborating with scientists to advance technology and support deployment in production systems.

As a Senior Perception Engineer, you will develop and deploy perception algorithms for self-driving vehicles, ensuring quality and collaboration within a multidisciplinary team, while publishing research findings.

The Cloud and DevOps Developer will implement DevOps best practices, design cloud solutions, collaborate with teams, and manage infrastructure projects.

Research Scientists at Waabi will lead AI projects to develop algorithms for self-driving technology, collaborate on solution deployment, and publish research at conferences.

The role involves defining and verifying vehicle platform requirements, enhancing capabilities, and ensuring safety compliance for self-driving technologies, while leading test campaigns and collaboration.

Design and develop motion planning software and algorithms for self-driving vehicles, collaborating with engineers and researchers while maintaining progress on long-term goals.

As a Performance Reliability Engineer, you will optimize performance and reliability of ML systems, analyze workloads, enhance collaboration with cross-functional teams, and influence architecture design.

As a Performance Engineer, you will optimize CPU and memory subsystems for high-performance ML workloads on x86 machines, develop algorithms for data movement, and engage with the AI community to enhance our AI platform.