Top Python Jobs in Toronto

Analyze product usage, feature adoption, telemetry, and financial data to generate actionable insights. Own data modeling, dashboards, KPI development, and end-to-end analytics delivery while partnering with stakeholders on product initiatives. Mentor associate-level analysts and maintain strong execution metrics for analytics work. The role requires advanced SQL and Python, Databricks and PySpark expertise, visualization experience, and SaaS product analytics experience.

Build and lead Replicant’s company-wide AI enablement program. Develop MCP integrations, shared agents, agent identity management, enterprise tool connections, reusable AI workflows, and cost-visibility mechanisms. Partner with Sales, Delivery, Finance, People, Engineering, and other teams to identify opportunities, implement solutions, promote AI literacy, and develop internal champions. Optimize AI systems through model routing, prompt caching, better agent design, and secure infrastructure.

Build Replicant’s internal AI enablement program by developing reusable agent workflows, MCP integrations, agent identity management, enterprise SaaS connections, and cost visibility mechanisms. Partner with Sales, Delivery, Engineering, Finance, People, and other teams to identify opportunities, implement secure AI solutions, create shared templates and skills, build AI literacy, and develop internal champions. Optimize AI infrastructure through prompt caching, model routing, tool consolidation, and improved agent design.

Design and implement enterprise contact center transformations using Amazon Connect, generative AI (Bedrock/Claude), serverless backends, and full-stack React tooling. Build contact flows, AI agents, CDK infrastructure, observability, CI/CD and migration solutions; collaborate with customers, mentor engineers, and ensure production reliability, security, and accessibility.

Design, build, and maintain Luminai’s core platform infrastructure, backend services, shared libraries, internal APIs, and deployment systems. Lead projects that improve scalability, reliability, developer workflows, CI/CD, testing, and local development. Strengthen production systems through secure authentication, access controls, secrets management, code review, testing, and maintainable engineering practices.

Design and deploy closed-loop decision systems that estimate causal effects, quantify uncertainty, and optimize actions under constraints. Develop policy learning, bandits/decision-making, counterfactual evaluation, and production ML infrastructure to drive measurable business lift and safe automated decisions.

Lead end-to-end data and ML pipelines for onboarding and fraud decisions: ingest streaming and batch sources, build feature platform and entity resolution, productionize ML models, enforce PII/data governance, and set technical direction while mentoring engineers and ensuring low-latency, reliable serving.

Build scalable automated solutions for device fleet management, own and optimize MDM platforms, write OS-level scripts for self-healing, gather telemetry to prevent end-user disruption, translate compliance (CMMC) into code-managed baselines, and create dashboards and alerts measuring end-user SLOs.

Manage daily Data team operations, research and analyze datasets, build internal and external reports (including an annual Startup Ecosystem Ranking), and maintain/improve Python scripts and data infrastructure to deliver actionable insights.

Build and deploy AI/LLM-powered features and RAG pipelines for internet-scale threat intelligence. Prototype, fine-tune, evaluate, and optimize models; integrate AI into platform services; implement CI/CD, regression testing, and security guardrails; collaborate across product, frontend, and data teams to deliver real-time, low-latency AI-driven analytics and automation.

Build and integrate LLM-powered applications and agents (RAG, vector DBs, agent orchestration) into the PureFacts SaaS platform, design evaluation and safety frameworks, implement APIs and scalable services, and partner with product and engineering to deliver AI copilots and automation that improve revenue analytics and operational efficiency.

Lead design, development, and deployment of ML/AI solutions across the PureFacts platform. Own ML product vision and MLOps for multiple client models, build scalable data pipelines and cloud-based deployments, embed AI-driven automation and LLM features, ensure governance and explainability, and mentor a team of ML engineers to deliver measurable business impact.

Build a vendor-agnostic agent platform and runtime primitives, implement evaluation, reliability, safety, and governance tooling, and develop data grounding, retrieval, and memory systems to support agentic workflows and model serving in production.

Lead technical strategy and hands-on development of large-scale optimization and ML systems (routing, scheduling, resource allocation). Design MILP/VRP/constraint solutions, integrate forecasting with optimization, deploy on cloud/lakehouse, mentor a data science team, and partner with stakeholders to deliver measurable operational improvements.

Design and deliver cloud and AI security solutions, provide architecture and automation code, build proofs-of-concept, advise customers, publish reference architectures and technical content, and support training and evangelism for Fortinet cloud products.

Own end-to-end analysis of payments, chargebacks, and user lifecycle to identify drivers of net loss. Deep-dive into fraud cases, design and evaluate A/B experiments and risk-rule changes, build monitoring dashboards, partner with Risk, Payments, and Product to convert insights into mitigations, and run ad-hoc analyses of emerging loss trends.

Lead post-silicon debug and bring-up for AI accelerator platforms, diagnosing hardware and firmware failures across chips, boards, and systems. Drive root-cause analysis for power, thermal, memory, high-speed links, PCIe and NoC issues; build debug tools, automation, and methodologies; collaborate with ASIC, firmware, and software teams to resolve complex system-level problems and improve reliability.

Hands-on IT generalist responsible for end-user support, POS (Oracle Simphony) and network (Cisco Meraki) administration across multiple restaurant sites, building automations (Python/Google Apps Script), performing preventative maintenance, and creating SOPs and documentation. Requires travel across the GTA and occasional evenings/weekends.

The DevOps Engineer will design, build, and enhance cloud and automation platforms, collaborating with development teams to implement secure and scalable DevOps solutions.

Own financial performance for a portfolio of clinics: forecasting, monthly reporting, owner payments, gross-margin/COGS optimization, and business partnering. Build AI-powered automations and models, drive actionable improvement plans, reconcile payments, and work closely with practice owners and success managers to deliver measurable P&L outcomes.

Lead global delivery of workflow, automation, and internal software solutions across 3–5 internal and third-party squads. Drive planning, capacity balancing, CI/CD, testing, release readiness, and operational support. Standardize delivery practices, enforce platform and architecture standards on Azure, Power Platform, and Microsoft Fabric, manage vendor SOWs, track delivery metrics, and communicate risks and status to technical and business stakeholders.

Architect and build core distributed systems for high-throughput real-time and batch data ingestion, processing, and storage. Ensure fault-tolerance, scalability, and strong query performance for time-series and spatial data. Develop automated tooling for data quality and lineage, collaborate on reusable abstractions, and write production-ready code (Java/Python).

Build end-to-end features for an agentic AI media manager: design APIs, backend services, agent logic, data models, and customer-facing interfaces; use AI coding tools, test and operate production systems, work directly with customers, and iterate on agent reliability, guardrails, and human approval flows.

Build and maintain cloud-native services, APIs, and platform capabilities. Design, implement, test, and troubleshoot scalable SaaS/backend systems. Collaborate with product, UX, and engineering teams, participate in code reviews, agile delivery, and continuous learning.

Lead production, analysis, and enhancement of the bank's Funds Transfer Pricing framework. Build and maintain Power BI dashboards, perform data testing and impact assessments, deliver insights to stakeholders, automate analytics, document data flows, and act as a trusted advisor to finance and business partners to support timely, accurate FTP rates and reporting.