Top Python Jobs in Toronto

Develops next-generation AI, machine learning, generative AI, and agentic AI solutions for engineering workflows. Responsibilities include researching techniques, evaluating approaches, building and validating production-ready applications, APIs, services, and data pipelines, and transitioning solutions to internal customers. The role also evaluates emerging technologies, supports R&D programs, coordinates innovation projects, analyzes engineering results, and collaborates with engineering teams, universities, suppliers, and strategic partners.

Supports global supply chain risk and resiliency by integrating supplier, BOM, sourcing, and manufacturing data. Models disruption scenarios, assesses production and revenue impacts, identifies mitigation options, automates recurring reports, and maintains Power BI dashboards. Collaborates with sourcing, manufacturing, IT, and supply chain stakeholders to improve data quality, traceability, dual-sourcing strategies, and business continuity planning.

Leads customer and partner engagements for Cadence timing signoff and closure solutions across advanced semiconductor nodes. Drives STA, IR Drop, power and timing closure benchmarks, flow optimization, tool adoption, and methodology deployment. Collaborates with R&D and product engineering, influences tool enhancements, leads technical programs, and represents Cadence through industry presentations and technical publications. Requires deep advanced-node signoff expertise, scripting skills, customer leadership, and familiarity with Cadence EDA tools.

Develop and deploy production-grade machine learning and AI solutions for fleet analytics, logistics optimization, forecasting, anomaly detection, predictive maintenance, and operational decision-making. Build batch and streaming pipelines, MLOps workflows, analytical data models, dashboards, and LLM-powered applications on cloud platforms. Collaborate with cross-functional teams to solve business problems and support model monitoring, experimentation, documentation, and data governance.

Build and deploy production AI agents and MCP integrations for logistics workflows including dispatch, billing, compliance, and fleet operations. Responsibilities include developing multi-agent systems, retrieval architectures using RAG, KAG, and CAG, LLM integration layers, domain tools, and Kubernetes-based infrastructure with GitOps and observability. The role also involves collaborating with cross-functional teams to translate operational requirements into reliable AI capabilities.

Own and administer the Okta IAM platform, including SSO, MFA, provisioning, governance, privileged access, and application integrations. Automate identity lifecycle processes using APIs, Python, or PowerShell; maintain Okta and Entra ID integration; and connect identity with Google Cloud IAM. Lead governance for AI agents, bots, service accounts, and workload identities, including ownership, least privilege, credential vaulting, and rotation. Develop developer-facing identity guidance.

Own the vision, strategy, and roadmap for Veeva Vault PromoMats capabilities, including claims management, MLR workflows, digital asset management, and AI automation. Conduct customer discovery, define requirements, measure product impact, and partner with Engineering, UX, QA, Sales, Services, and Support to deliver compliant, scalable solutions. The role requires enterprise product management experience, hands-on LLM and generative AI expertise, Python coding, AI framework knowledge, and familiarity with marketing operations and regulated life sciences workflows.

Leads administration, deployment, migration, monitoring, tuning, security, backup, replication, failover, and disaster recovery for on-premises and Azure SQL databases. Troubleshoots production issues, automates DBA tasks with PowerShell and Python, supports application and development teams, manages database changes, and provides documentation and after-hours support.

Build and maintain trusted analytical datasets, data marts, semantic models, certified metrics, and reusable data products. Develop scalable ELT transformations, data quality controls, testing, and governed business logic that support enterprise reporting, business intelligence, advanced analytics, and AI initiatives. Partner with technical and business teams, guide design practices, mentor colleagues, and translate requirements into reliable data solutions.

Lead Securian Canada’s enterprise analytics strategy, business intelligence, analytics engineering, and AI initiatives. Build scalable data products, KPI frameworks, semantic models, dashboards, and decision-support solutions. Advise executives, translate complex business challenges into actionable insights, establish responsible AI and data governance practices, and lead a multidisciplinary team while developing talent and fostering data-informed decision-making across the organization.

Build and ship full-stack product features across React, TypeScript, Django, Python, GraphQL, and related systems. Own features from technical planning through rollout, monitoring, and iteration. Collaborate with Product and Design, write tests, review code, troubleshoot user issues, and improve performance and reliability. Use AI coding agents and develop agentic workflows that improve engineering productivity while contributing to technical discussions and shared practices.

Leads complex implementation, onboarding, configuration, testing, validation, and go-live activities for Enable’s enterprise pricing and rebate software. Manages customer engagements, workshops, troubleshooting, risks, escalations, and change management while ensuring solutions meet agreed requirements. Serves as a technical lead, mentors associate consultants, supports customer adoption, identifies training and expansion opportunities, and collaborates with multifunctional project teams.

Develops, deploys, and monitors production data and machine learning pipelines. Responsibilities include data preparation, exploratory analysis, predictive modeling, feature and algorithm selection, model deployment, infrastructure development, and monitoring model performance, data quality, drift, latency, and reliability. The role also requires communicating insights, collaborating cross-functionally, and translating business problems into scalable data and ML solutions.

Develop and maintain full-stack software solutions using .NET and related web technologies. Responsibilities include feature development, unit testing, code reviews, incident support, troubleshooting, system documentation, application integration, quality assurance, and collaboration with technology and business stakeholders. The role also supports continuous improvement, automation, risk management, and mentoring while ensuring solutions meet architectural, performance, security, and regulatory standards.

Designs, develops, and maintains enterprise ETL solutions using Informatica, SQL, cloud platforms, and data warehousing practices. Builds scalable data pipelines, integrates Salesforce and other enterprise systems, monitors data quality and performance, troubleshoots issues, and supports cloud modernization. Collaborates with business and technology teams in a regulated financial services environment while contributing to technical standards, documentation, governance, and mentoring junior developers.

Own analytical workstreams supporting strategic and operational decisions. Partner with stakeholders to define questions, conduct exploratory and quantitative analyses, evaluate initiatives, develop metrics and dashboards, and translate findings into actionable recommendations. The role uses SQL, Tableau, Python, experimentation, segmentation, cohort analysis, scenario analysis, and impact measurement while collaborating across Analytics, Business Intelligence, Analytics Engineering, and Data Science.

Senior Data Scientist supporting Canadian business units to design, develop, and deploy ML and GenAI solutions (including agents, chatbots, RAG, and vector-based retrieval). Translate business goals into analytics, perform feature engineering, model training/evaluation, prompt engineering, and mentor junior staff. Provide technical leadership, design artifacts, stakeholder communication, and drive continuous improvement.

Manage compliance data by designing and optimizing databases, data models, governance processes, dashboards, reports, and visualizations. Use Power BI, Python, VBA, SQL, and Microsoft Power Platform to automate processes, improve data quality, and strengthen controls. Collaborate with Compliance and Technology stakeholders to deliver secure, reliable data assets and tailored analytics solutions while supporting data architecture, metadata, access management, and the data management roadmap.

Owns the technical and statistical integrity of payment data analytics workflows. Responsibilities include SQL and Python data ingestion, transformation, validation, quality controls, feature engineering, time-series analysis, model readiness, back-testing support, GCP analytics environment management, workflow automation, documentation, and translating findings for product and executive stakeholders.

Leads multiple engineering teams developing AI and machine learning solutions, including LLM and RAG architectures. Sets technical direction, oversees hiring and development, manages budgets and resources, establishes engineering standards, resolves complex issues, and aligns delivery with senior stakeholders. The role requires hands-on Java, Python, machine learning, NLP, cloud, containerization, and Kubernetes expertise.

Leads engineering strategy, platform modernization, and delivery for wholesale lending technology platforms supporting loan origination, servicing, syndication, collateral management, and workflow automation. Oversees distributed systems, APIs, Kafka-based event pipelines, cloud infrastructure, CI/CD, security, testing, and resilient releases. Recruits and mentors engineering teams, partners with product, risk, operations, and architecture stakeholders, and drives adoption of GenAI development tools and modern engineering practices.

Design, develop, test, deploy, and maintain Java and Spring Boot backend services and microservices. Implement automated testing, CI/CD pipelines, deployment automation, secure coding practices, and version-control workflows. Troubleshoot production issues, contribute to code reviews, documentation, architecture modernization, and technical debt reduction. Collaborate with product, architecture, DevOps, QA, and technology teams in an Agile environment while supporting compliance and risk-management objectives.

Design and deploy enterprise AI agents and cloud-native systems using retrieval, orchestration, tool invocation, policy routing, evaluation, and observability. Integrate multiple AI providers, build scalable microservices and production infrastructure, lead client workshops and proofs of concept, define quality and cost metrics, and create reusable engineering patterns. This hybrid role requires three days weekly in the Mississauga office.

Develop and maintain scalable VFX pipeline systems and production tools across departments. Provide technical support to artists, troubleshoot workflow issues, automate repetitive tasks, research technologies, document tools, and contribute to Agile sprints. The role requires strong Python development, pipeline infrastructure, CI/CD, package management, DCC integration, and Qt/PySide UI experience in a VFX or animation studio environment.

Provides Tier 3 Linux systems support for clients, including troubleshooting, alerts, patching, health checks, deployments, infrastructure roadmaps, cloud management, networking, containers, Kubernetes, virtualization, backups, and disaster recovery. The role involves client communication, onboarding, ticket and time tracking, independent problem-solving, documentation, and occasional after-hours support in a fully remote environment.