Top Python Jobs in Toronto

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, 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, 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 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.

Develop and validate mathematical models for pharmaceutical and biologics manufacturing. Collaborate with customer SMEs and cross-functional teams to translate process challenges into simulation and control solutions, implement research-grade Python code, document model structure, and support product roadmaps and best practices for process simulation.

Design, develop, and maintain Power BI dashboards, data models, and ETL for inventory management. Integrate ERP/WMS data, ensure data integrity and performance, document KPIs, support stakeholders, train end-users, and use Python for advanced analysis and automation to drive inventory optimization and reporting.

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.

Design, build, and maintain scalable automation solutions for analytics and reporting. Partner with stakeholders to streamline processes, develop backend and frontend automations, optimize SQL databases across cloud and on-prem, leverage BI and automation tools (Power BI, Alteryx, KNIME), measure automation ROI, support project initiatives, and mentor junior team members.

Develop and maintain sales forecasting models, analyze performance trends, and build dashboards in Power BI/Looker. Translate statistical analysis into actionable insights, present findings to stakeholders, ensure data governance, automate processes, and validate data to drive business decisions across Finance, Sales, and executive leadership.

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 active management of public corporate bond portfolios (mainly Investment Grade), generate relative-value outperformance, monitor performance versus benchmarks, collaborate with research/trading, present strategies to committees, drive process improvements, lead projects, and coach junior team members.

Design, implement and maintain backend systems for a financial platform. Collaborate with quants, frontend and platform teams to build cloud-native AWS services, HTTP APIs and event-driven microservices using Rust and Python. Model complex financial trades, work with MySQL, MongoDB and other databases, and support performance-critical systems and observability.

Design, develop, and maintain data engineering solutions across the SDLC using Python (primary) and Scala (secondary). Build distributed data pipelines on Hadoop/Spark ecosystems, extend data processing platforms (Spark SQL, Hive, Starburst), manage CI/CD, and deploy on Kubernetes/OpenShift. Collaborate with stakeholders in Agile teams and ensure maintainable, reusable code.

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.

Contribute to end-to-end deployments of Conductor: build and integrate full-stack services (backend in Python/TypeScript), implement agentic workflows and adapters for healthcare systems (HL7, FHIR, DICOM, RIS/PACS), diagnose production issues using logs and telemetry, and create integration libraries, runbooks, and product feedback from client deployments.

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.

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.

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.

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.