Top Python Jobs in Toronto

Develop and automate configuration for distributed clusters, create monitoring tools, manage cloud operations, and ensure system reliability for Cerebras AI supercomputers.

Embed with cross-functional teams to map high-value workflows, design agentic or deterministic automated solutions, build production-ready tools, and run them with monitoring, evals, and continuous improvement. Balance stakeholder discovery, systems integration, full-stack development, and operational ownership to increase throughput and reduce cost.

Develop and deploy scalable deep learning and reinforcement learning systems, optimize performance, and collaborate with data teams at Quincus.

The Site Reliability Engineer will enhance operational reliability, managing incidents, improving system performance, and maintaining metrics to ensure scalability and resilience.

The DevOps Engineer will enhance CI/CD workflows, manage AWS infrastructure, automate operations, and improve system reliability and monitoring.

Lead design, implementation, and management of CI/CD, container platforms, IaC, and observability. Build pipelines with Tekton and Harness, administer OpenShift/Kubernetes, automate provisioning with Terraform/Ansible, and monitor systems with Prometheus/Grafana. Collaborate with development teams, ensure resiliency/scalability/security, drive platform strategy, perform root cause analysis, and enforce compliance and quality standards.

Design, build, and maintain scalable data pipelines and enterprise AI agents using Python, FastAPI, PySpark, Kafka, and Databricks. Deploy GenAI agents with Google ADK/Flash LLMs, build data federation and Data Mesh layers (Starburst), automate microservice integrations on cloud-native platforms (OpenShift/Kubernetes) with CI/CD, and integrate agentic tools (Devin.AI, GitHub Copilot, MCP) via prompt engineering. Ensure data quality, security, and regulatory compliance while improving data engineering processes.

As a Machine Learning Engineer, you will develop models for NLP and code-generation systems, analyze data, and improve AI performance using advanced algorithms. You'll manage the entire ML lifecycle and ensure effective communication of model benefits across the organization.

As a Senior Deployment Engineer, you'll manage the deployment lifecycle of Atolio's enterprise search platform in diverse environments, ensuring scalability and security while collaborating with internal and client teams.

Lead technical SEO for content marketing: conduct technical audits, improve search and AI visibility (GEO/AEO), run SEO reporting and recommendations, and build AI-assisted workflows for content production and analysis.

As a Backend Engineer, you will architect, build, and deploy systems for our data science platform, collaborating with a cross-functional team to enhance machine learning practices.

Seeking Data Platform Engineers to design, build, and manage scalable data pipelines and analytic query engines while ensuring data integrity and performance optimization.

As a Backend Software Engineer, you'll develop critical backend systems focusing on APIs, data processing, and infrastructure while ensuring high-quality service delivery and robust architecture.

Lead development of backend systems and integrations to ingest and process large-scale data, design secure multi-tenant SaaS architectures, own APIs and platform work, mentor engineers, author technical proposals, and troubleshoot production issues to minimize downtime.

Lead structuring and execution of structured financings (RMBS, ABS, master trust, asset sales), develop a secondary trading platform, manage interest-rate and credit risk, build cash-flow models and analytics (Intex/Excel), execute go-to-market financing strategies, and provide investor, rating agency, and capital provider support.

Lead end-to-end AI solutions as a forward-deployed engineer: scope, design, and deploy ML/LLM systems; partner with clients and stakeholders; build infrastructure, data pipelines, and reusable platform components; mentor engineers; own projects from discovery through production and provide on-call support.

Configure and maintain legal technology platforms, build integrations and automated workflows, develop AI-assisted tools and dashboards, analyze operational data, and drive process improvements across the legal function while collaborating with IT, Product, and AI teams.

Build and own end-to-end fullstack features for a marketing analytics dashboard. Lead technical direction, collaborate with product and customer teams, optimize frontend performance, create and maintain APIs, ensure reliability and scalability, and mentor other engineers.

As a Senior Full Stack Software Engineer at Doxel, you will design and develop applications for project management, focusing on complex data handling and intuitive UI. Your role involves collaborating across teams and providing technical leadership in software projects.

Design, build, and operate backend systems and infrastructure. Work on system design, databases (SQL/NoSQL), cloud platforms, containerization, IaC, CI/CD, monitoring/logging, networking, security, and Linux fundamentals in a fast-paced startup environment.

Build end-to-end features across frontend and backend for the Mem0 platform using Next.js and Python. Design APIs, UIs, backend services, and data models; optimize performance and reliability; write tests and operate production systems; collaborate with design, research, and customers to deliver scalable AI memory product experiences.

Lead development of cloud data platforms and end-to-end data pipelines using AWS/Snowflake and big-data technologies (Spark, Hive, Iceberg). Automate builds and deployments with Bash/Python shell scripting, apply CI/CD and Medallion Architecture, perform data modeling and warehousing, and collaborate across teams. Pharma/AbbVie experience preferred.

Design, build, and deploy AI agents and automations to streamline pre-sales processes (discovery, demos, RFPs, POCs). Integrate AI tools with CRM and knowledge systems, prototype quickly, train and support solutions engineers, monitor automation performance, and document scalable workflows to improve adoption and impact.

Build and scale a live ML data streaming analytics platform, lead greenfield real-time processing projects (Python/Rust), and design reliable backend services using cloud and orchestration tools.

Lead quality strategy and testing for LLM-powered and agentic systems. Design evaluation frameworks, build scalable automated test suites, define quality metrics, integrate tests into CI/CD, mentor QE org, and partner with cross-functional teams to ensure release readiness for AI products.