Top Python Jobs in Toronto

Designs, builds, governs, and supports AI-powered copilots, agents, automations, analytics, scripts, and low-code solutions for workplace technology services. The role analyzes business processes, develops secure integrations, applies responsible AI and governance controls, performs testing and monitoring, creates documentation, and supports adoption. It also provides targeted workplace technology support, incident management, and operational continuity using ITIL practices.

Lead architecture and end-to-end delivery of large full-stack projects for MaintainX’s core work execution platform. Shape technical direction, design scalable workflows, mentor senior and staff engineers, improve reliability and delivery practices, and partner with product, design, and engineering leadership. Work across dense data interfaces, mobile-first experiences, offline behavior, multi-site scale, scheduling, inventory, reporting, and enterprise systems while participating in on-call rotation.

Lead the architecture and delivery of shared platform and infrastructure systems, including APIs, developer tooling, design system components, release foundations, and runtime services. Own technical direction, reliability, performance, and long-term health for a platform domain. Partner across product and engineering teams, mentor senior engineers, drive adoption, improve testing and delivery practices, and participate in on-call rotations.

Develop and maintain scalable Java applications and REST APIs using Spring Boot. Write clean, efficient code, automate tasks, test using TDD, troubleshoot systems, monitor performance, and collaborate with internal teams and vendors. Review code, validate software, apply current technologies, and contribute to product improvements. The role may also involve cloud platforms, containers, CI/CD, security protocols, UI frameworks, on-call support, and mentoring.

Own capital markets and corporate treasury operations, including loan-level and portfolio reporting, borrowing base and waterfall calculations, facility covenant compliance, cash and liquidity forecasting, lender reconciliations, servicing invoices, and financial models for funding facilities and capital raises. Support FP&A, month-end close, audit, tax, budgeting, and Board reporting while collaborating across the Finance team.

Build, train, evaluate, and deploy production machine learning and LLM systems for legal document intelligence. Develop NLP solutions for information extraction, summarization, search, AI agents, and document analysis. Create scalable ML pipelines, evaluation frameworks, and reliability metrics while optimizing model performance. Collaborate with engineering, product, legal, data, and security teams to deliver secure AI capabilities and translate business problems into production solutions.

Design and lead enterprise AI systems using generative AI, RAG, knowledge graphs, and autonomous agents. Define technical strategy, evaluate emerging AI technologies, and guide architecture and roadmaps. Mentor engineers, champion MLOps and LLMOps governance, and ensure security, testing, monitoring, and observability. Collaborate with research, engineering, design, and product teams to deliver scalable customer-facing solutions while optimizing latency, cost, and user experience.

Leads the architecture, development, deployment, and maintenance of Azure-based data platforms and products. Designs infrastructure using Terraform, builds secure CI/CD pipelines, develops scalable data pipeline templates, and implements monitoring, quality, reconciliation, governance, and security controls. Provides engineering leadership, mentors staff, coordinates platform updates, optimizes performance, documents systems, and partners with business, technology, security, governance, vendors, and analytics teams to deliver customer-centric data initiatives.

Leads SRE and DevOps delivery for reliable, scalable services across AWS and Azure. Responsibilities include Kubernetes operations, GitHub Actions CI/CD, observability with Datadog, cloud security guardrails, policy-as-code, incident automation, and AI-enabled operations using Bedrock, SageMaker, and MCP. The role supports Linux, Windows, IIS/.NET, and Java Spring Boot environments while partnering with development, operations, security, and risk teams.

Build, operate, and optimize AWS-based data ingestion pipelines from Aurora MySQL into Snowflake. Responsibilities include infrastructure engineering, reliability and observability, SLOs, incident response, infrastructure as code, CI/CD, performance and cost tuning, source onboarding, and security controls for payment-compliant environments. The role also involves applying AI tools to improve development, testing, runbooks, and documentation.

Designs and leads enterprise AI systems for legal research, including RAG pipelines, knowledge graphs, autonomous agents, and AI platforms. Provides technical strategy, architecture, mentoring, governance, testing, observability, and operational leadership. Partners with research, engineering, design, and product teams to launch scalable, secure AI products. Requires hands-on software engineering expertise in generative AI, cloud-native systems, APIs, distributed systems, and production AI deployments.

Analyzes propane supply costs, pricing, market conditions, margins, and commercial performance across Canada. Builds reports, dashboards, forecasts, and analytical tools using Excel, SQL, Python, and AI technologies. Supports hedging analysis, market research, acquisition screening, executive presentations, audits, and process improvements while partnering with Supply, Finance, Sales, and branch operations.

Lead reliability and platform engineering for mission-critical Fitch Ratings services, focusing on Kubernetes, cloud infrastructure, CI/CD, observability, security guardrails, and AI-enabled operations. Build GitHub Actions pipelines, define SLOs and telemetry, automate incident response, support AWS and Azure environments, and guide development squads on deployment and operational excellence. The role also supports AI/ML workloads, policy-as-code, compliance automation, and secure infrastructure practices.

Validate retail credit risk, stress-testing, capital, marketing, and analytics models. Develop independent benchmark models using statistical and machine-learning techniques, assess assumptions and implementation accuracy, document validation results and limitations, and provide management recommendations. Collaborate with model development teams and external vendors while monitoring evolving risk-management methodologies and regulatory requirements.

Leads second-line AI risk monitoring and independent review programs, establishing frameworks, metrics, dashboards, controls, evidence standards, and escalation processes. Monitors AI performance, drift, emerging risks, governance, and control effectiveness across the AI lifecycle. Provides independent challenge, supports audits and regulatory examinations, tracks remediation, advises stakeholders, and reports risk trends and program effectiveness to senior management and governance committees.

Aggregates, organizes, and analyzes trade data for client-level reporting and business insights. The role collaborates with trading, risk, finance, technology, and operations teams; troubleshoots issues; and provides recommendations to senior stakeholders on strategic initiatives, transaction structures, product development, and infrastructure improvements.

Lead the end-to-end data science lifecycle for multiple business use cases, including data extraction, wrangling, feature engineering, statistical modeling, machine learning, evaluation, deployment, and change management. Partner with business stakeholders to identify opportunities, recommend solutions, assess model fairness and risk, and integrate predictions into underwriting, claims, customer experience, and risk processes. Collaborate with IT Services to establish MLOps for batch and real-time prediction services.

Lead credit modeling and strategy for Flexiti’s Buy Now, Pay Later account management business. Develop, monitor, and enhance credit strategies and statistical or machine learning models; analyze data; build risk, delinquency, and profitability dashboards; identify process improvements; and ensure model governance and documentation comply with OSFI requirements. The role also involves leading direct reports, escalating material credit risks, and collaborating with cross-functional partners.

Own the readiness and reliability of deployed data-capture devices. Diagnose hardware and software issues across cameras, peripherals, Linux systems, storage, networking, and data transfers; prepare and validate devices for deployment; support operators; reproduce defects; create diagnostic scripts and procedures; track recurring failures; and verify repairs, updates, and corrective actions across the device fleet.

Leads the design, development, integration, and maintenance of enterprise-scale data applications and pipelines using Databricks, Azure Data Factory, Informatica, Oracle, Python, and SQL. Develops technology roadmaps, leads complex projects, conducts code reviews, mentors developers, and delivers scalable solutions aligned with business objectives. Responsibilities also include data integration, CI/CD, API development, batch scheduling, secure file transfers, and technical leadership.

Leads business data analysis, reporting, performance measurement, predictive modeling, and dashboard development for government contract programs. Extracts, cleanses, analyzes, and governs data from multiple sources using Power BI, Excel, SQL, Python, and R. Translates complex findings into strategic insights, ensures reporting and contractual compliance, improves reporting processes, and collaborates with cross-functional teams to support data-driven decisions and program outcomes.

Leads the end-to-end development and deployment of AI/ML models for enterprise financial reconciliation and data engineering. Designs Agentic AI and Generative AI solutions, analyzes structured and unstructured financial data, defines model roadmaps, and integrates models into production. Partners with engineering and business teams on scalability, risk mitigation, documentation, and adoption while translating complex findings into visualizations and strategic recommendations for senior leaders.

Designs enterprise-scale data processing frameworks and Azure-based data solutions, develops AI-powered automation, leads complex technical initiatives, mentors engineers, and influences data engineering strategy. The role requires advanced Python, Azure data services, data warehousing, distributed computing, and architecture expertise, along with stakeholder collaboration and technical leadership.

Leads counterparty credit risk analytics, exposure measurement, model governance, regulatory and stress testing deliverables, data controls, automation, and team leadership. Provides insights on PFE, settlement, MTM, CVA, collateral, netting, wrong-way risk, and trading exposures while partnering with risk, trading, model validation, and technology teams.

Own and improve production cloud platform operations on Azure, with a focus on AKS, networking, infrastructure automation, deployment reliability, observability, and incident readiness. Design Terraform-based infrastructure, strengthen GitOps and CI/CD workflows, troubleshoot complex production issues, and establish operational guardrails. Serve as a senior escalation point for high-severity incidents, lead root cause analysis, mentor Cloud Operations engineers, and collaborate with Engineering, SRE, Security, and Delivery teams.