Top Python Jobs in Toronto

Lead commercial P&C pricing and predictive analytics efforts: maintain and enhance SAS-based pricing tools, collaborate with Data Science and underwriting to develop and validate models, deliver data-driven pricing recommendations, support small business pricing, mentor junior analysts, and drive process improvements and automation.

Analyze and transform claims and financial data to deliver insights, automate data-science workflows, identify opportunities to improve claims payment accuracy and reduce expense, benchmark performance, and collaborate with Claims, Actuarial, Pricing, Data Science, Underwriting and Risk to influence operational improvements.

Design, develop, and maintain backend microservices for reporting, analytics, data export and data-driven features. Collaborate with product, data, and engineering teams, implement APIs for BI tools, ensure data quality/governance, participate in design reviews, mentor junior engineers, and support agile delivery.

Lead architecture and implementation of scalable analytics, reporting, and AI-driven data intelligence capabilities. Own end-to-end services, drive technical direction, mentor engineers, ensure operational excellence, and collaborate with product and design to deliver secure, high-performance, maintainable solutions using cloud-native and data-platform technologies.

Lead design, build, and maintenance of User Domain and HRIS integration services handling millions of user records. Architect scalable, secure microservices, mentor engineers, own features end-to-end, collaborate cross-functionally, and improve performance, reliability, and tooling.

The role involves designing and tuning control systems for robotics, integrating hardware, developing control algorithms, and collaborating with engineers to enhance robot motion and responsiveness.

Lead development and execution of payment fraud strategies. Investigate and monitor fraudulent activity, perform SQL-driven analytics and root-cause reporting, build and deploy fraud detection models, and collaborate with product, engineering, and vendors to implement automated fraud controls.

Design, prototype, and productionize machine learning models for real-world problems using structured and unstructured data. Implement scalable ML systems, apply statistical methods, rapidly prototype research papers, and collaborate with engineering teams to deliver data-driven solutions.

Lead data science engagements: partner with client executives, identify high-impact projects, design end-to-end data pipelines and models, build KPIs and production dashboards, mentor teams, and deliver scalable data products driving business impact.

Design, build, and optimize ETL pipelines, data schemas, and data tools to support analytics and data science. Tune SQL and databases for performance and collaborate with teams to scale data infrastructure using Snowflake, Python, and related tools.

Design, prototype, and productize scalable machine learning solutions using LLMs. Collaborate with clients and teammates to build production-ready systems, rapidly iterate prototypes, apply statistics and ML, and implement tooling and infrastructure for deployment and model-driven features.

Design, prototype, and productionize machine learning models from structured or unstructured data, build data products for business insights, and apply statistics and ML theory to solve client problems.

Design, build, and maintain production data infrastructure and pipelines; automate workflows; enable cross-team data access; perform large-scale data wrangling, statistical analysis, and visualization to deliver business insights.

Embed with partner health systems to deploy and customize Signal 1's AI Management System (AIMS). Connect to secure data, build monitoring and governance for predictive, generative, and agentic AI, develop bespoke agentic solutions, coordinate stakeholders, and convert field learnings into reusable platform components to improve safety and reliability in clinical workflows.

Analyze and redesign business processes, identify automation opportunities, and build low-code RPA workflows (UiPath, Power Automate). Collaborate with stakeholders and developers for integrations, document designs and benefits, and provide occasional after-hours support.

Lead design and delivery of production-grade AI/LLM platforms and assets to automate controls across Claims, Underwriting, Finance, and Technology. Build scalable ML pipelines, inference and serving, RAG and agentic solutions, ensure security/privacy/compliance, optimize cost and performance, and enable regional teams to operationalize AI capabilities.

The AI Engineer will design and develop scalable AI solutions for finance, ensuring compliance and collaboration across teams. Responsibilities include coding, model lifecycle management, automation, and technical mentoring.

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 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.

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.

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.