Top Python Jobs in Toronto

Lead end-to-end technical implementations of imaging solutions across hospitals. Design and troubleshoot integrations (DICOM, HL7, PACS/RIS), work with VPNs and APIs, mentor junior engineers, drive product/engineering improvements, create documentation and automation, and act as escalation for complex support issues.

Own the data platform product portfolio, prioritize datasets and capabilities, define schemas and governance, partner with engineering and analytics, enable trusted consumable data, run discovery with domain experts, track data health and adoption, and drive cross-team alignment to support downstream products and analytics.

Design, build, and maintain scalable AI platform infrastructure and services. Develop RESTful APIs, implement CI/CD for model deployment, ensure observability and container security, use generative AI tools in development, collaborate across teams, apply TDD and monitoring to deliver reliable, high-performance AI-enabled software.

Build, deploy, and support AI agents and intelligent workflows on Microsoft Azure and other enterprise AI platforms. Design orchestration, integrate LLMs, implement APIs and RAG/vector DBs, ensure responsible-AI guardrails, collaborate across product and operations, and monitor production AI workflows.

Work on building production-ready agentic AI applications and the Continuum platform: agent orchestration, model routing, persistent memory, tool integrations, retrieval pipelines, guardrails, evaluation, observability, and backend/APIs. Write well-tested Python code and contribute to open-source examples and documentation.

Design, analyze, test, and support development and production of star tracker optical systems. Build and commission test setups, collect and analyze performance data, assist quality and production teams with root cause analysis and integration, and support business development customer responses.

The role involves leading engineering teams in product development, driving innovation in software architecture, and integrating AI tools while providing mentorship and technical authority.

Lead supply analytics projects: translate briefs into analyses, query large-scale data warehouses, build dashboards and models, run experiments (A/B testing), identify growth opportunities, automate operations, and present data-driven recommendations to stakeholders and senior leadership. Hybrid Toronto role requiring coordination with regional partners and occasional evening meetings.

Lead design, build, and integration of production-grade AI systems into the marketing stack to drive personalization, automation, and measurable pipeline growth. Own martech strategy, governance, integrations (Marketo, Salesforce, GA4, CMS, DAM), LLM-enabled agents and vector retrieval, ML forecasting, performance monitoring, and cross-functional alignment with IT, Legal, Security, and Analytics.

Partner with Supply stakeholders to design and run analytical projects, build forecasts and statistical/ML models, run A/B tests, create dashboards and data products, automate manual processes, and deliver actionable insights to improve supply performance and operational efficiency.

Lead architecture and delivery of an internal AI/agent platform used across product teams. Design agent runtimes and SDKs, define release gates (evals, safety, telemetry, AuthX), set standards for prompt management and model selection, partner with product teams to integrate reusable platform capabilities, write and ship production code, and mentor engineers to raise company-wide production quality for agentic systems.

Lead GenAI strategy and delivery: identify automation opportunities, design and scale RAG and agentic AI solutions, integrate RPA/IPA and orchestration, build LLMOps pipelines, prototype autonomous assistants, and drive adoption across product, engineering, and business stakeholders while ensuring governance and documentation.

As a Data Scientist, develop machine learning models to support trading strategies, collaborate with teams, analyze data, and improve trading performance.

Design, build, and operate production-grade AI automations and integrations across marketing, operations, creative, and logistics. Develop AI-agent architectures and MCP servers, connect APIs and platforms, write Python/JavaScript, evaluate vendor tools, ensure security and reliability, and drive adoption via training and documentation.

Design and govern enterprise network architecture across on‑prem, hybrid, and cloud environments. Define standards, security segmentation, and automation using Terraform, Ansible, and scripting. Lead adoption of SD‑WAN and SASE, oversee Cisco, F5, and Palo Alto platforms, partner with cross‑functional teams, and act as SME/escalation lead to ensure secure, resilient network services for merchant traffic.

The Lead Research Engineer will provide technical leadership, develop scalable ML solutions, and collaborate with teams to innovate and deliver products that enhance customer experiences in legal, accounting, and government sectors.

Design, build, and deploy production-grade legal AI solutions by translating legal user needs into robust software. Collaborate with AI engineers, apply prompt/LLM evaluation, use DevOps and Infrastructure-as-Code, practice TDD, mentor junior engineers, lead agile projects, and deliver end-to-end solutions for law firms and legal departments.

Develop and optimize fabrication processes for integrated photonic devices (especially thin‑film lithium niobate). Own wafer lots with foundry partners, design and run process improvement experiments, perform metrology and failure analysis, collaborate across process and design teams, and implement new fabrication learnings to improve device performance.

Lead the architectural vision and technical strategy for eBay's Data Platform, focusing on building scalable and cost-efficient data systems and platforms.

Operate and modernize a large-scale RHEL estate across on-prem and cloud. Build automation (Ansible, Python, Bash, GitHub), manage virtualization (vSphere, Nutanix, Azure IaaS), maintain platform lifecycle and security (patching, upgrades, PKI, AD/sssd), support incidents/changes in ServiceNow, produce documentation and run rotational on-call for 24/7 production systems.

As a full-stack software engineer intern, you'll collaborate with senior engineers to write quality code, build AI-driven products, and improve engineering productivity.

Design, standardize, automate, and modernize on-premises and hybrid infrastructure. Build IaC and automation (Ansible, Terraform, Python, PowerShell), harden RHEL and Windows images to compliance baselines, act as Level 3 SME across compute, storage, virtualization, and identity, participate in ITIL processes, and collaborate with security, SRE, and architecture teams on upgrades, migrations, and compliance.

As Engineering Manager, you will manage a technical team, drive technical strategy, mentor developers, and ensure effective product delivery while aligning with organizational goals.

Administer and integrate core SaaS and collaboration platforms, build and maintain NetSuite and other system integrations, automate workflows with scripting, manage user lifecycle and SSO, support macOS/Linux/Windows endpoints and hardware, triage and resolve support tickets end-to-end, maintain documentation and runbooks, and participate in on-call rotation.

Design and implement backend services and data pipelines to match business activities to context. Perform data-driven research, build scalable ML/LLM systems, write tests, create observability and runbooks, and collaborate across teams to deploy and operate production services.