Top Python Jobs in Toronto

Develop, integrate, and validate IVI software for AFEELA vehicles across applications, middleware, and OS components. Debug, test, and optimize performance; support UI/UX implementation, partner developer support, demo vehicle setups, and cross-regional collaboration while ensuring automotive safety compliance.

Lead the development of a platform for fast, high-quality deployments in universities, focusing on security, data engineering, and automation.

The Founder's Associate will manage company operations, support internal tools and projects, and ensure the founders can focus on growth. Responsibilities include CRM management, financial modeling, and project tracking, requiring strong organizational skills and coding experience.

The Forward Deployed Engineer will manage customer deployments, handling all aspects from initial contact to ensuring successful usage, including data engineering, backend services, frontend development, and customer training.

Design and maintain data warehouse systems, develop ETL pipelines, manage datasets for analytics, and implement real-time data solutions.

The Data Scientist will design algorithms for insights, structure data, collaborate with machine learning engineers, and analyze datasets to improve workflow automation and product value.

Develop and optimize AI pipelines for workflow intelligence, experiment with models, and collaborate to integrate AI systems into workflows.

You will build and maintain features across frontend and backend stacks, design analytics dashboards, optimize APIs, and ensure database performance while collaborating with various teams.

This role involves leading enterprise clients in enhancing their Microsoft 365 collaboration using AI technologies, while also ensuring security and compliance. The consultant will architect, implement, and govern solutions such as SharePoint Online and manage AI integration.

Build high-performance, scalable simulation infrastructure and tooling for autonomous vehicle development. Design systems for scenario generation, simulation execution, synthetic data, and reinforcement-learning workflows. Collaborate with ML, perception, and controls teams to improve realism, performance, and validation pipelines while writing production-quality C++ and Python code, contributing to architecture, testing, and documentation.

Lead budgeting, forecasting, and variance analysis while building AI-driven financial models, scenario planning, KPIs, and dashboards. Automate FP&A processes, deliver insights to senior leaders, and collaborate with cross-functional teams to improve forecast accuracy and strategic decision-making.

Design, implement, and optimize AI-driven solutions across the claims lifecycle (intake, investigation, adjudication). Build ML models for data extraction, fraud detection, reserve setting, subrogation, and adjudication decision engines. Collaborate with underwriting, fraud, legal, and IT to integrate models into operations and improve efficiency, accuracy, and compliance.

Drive data-informed capital allocation by building financial models (NPV, IRR), applying AI/ML for forecasting and scenario planning, creating build-vs-buy and prioritization frameworks, implementing decision-support systems, collaborating with cross-functional stakeholders, and monitoring post-investment performance to refine allocation models.

Design, implement, and monitor AI/ML models to improve underwriting risk assessment, pricing, and portfolio management. Translate underwriting rules into data models, integrate models into workflows, analyze datasets for risk patterns, build decision-support tools, ensure compliance and fairness, and collaborate with underwriting, actuarial, product, and engineering teams.

Lead modernization of month-end and year-end close processes using AI and automation. Prepare, review, and validate journal entries, accruals, and financial statements. Implement anomaly detection, automated reconciliations, variance analysis, and predictive insights. Collaborate with data teams to structure finance data for ML use cases and design audit-ready, scalable reporting workflows.

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

Design and implement AI/NLP solutions to automate insurance policy administration (issuance, endorsements, renewals). Translate policy language into models and rule engines, integrate with PAS, ensure regulatory compliance, monitor model performance, and support underwriting, operations, and exception handling.

Lead AI-enabled financial planning and strategic analysis, build data-backed business cases, refine unit economics, deliver executive-level insights, integrate ML into FP&A, and track KPIs to drive profitability and strategic decisions.

Lead integration of AI-driven tools into tax provision, planning, and multi-jurisdictional compliance. Design ML/analytics solutions for sales and payroll tax, enhance regulatory filings, support audits, and collaborate with finance, legal, and technology teams. Monitor tax regulation changes, document AI tax models for transparency and governance, and continuously refine models for scalability, reliability, and compliance.

Build and maintain operating and cash-flow models, apply AI/ML and data techniques to automate forecasts, run sensitivity and scenario analysis, translate strategy into financial outcomes, support fundraising/M&A/pricing, and create dashboards and reports for stakeholders.

The Machine Learning Engineer will design, develop, and deploy ML pipelines, optimize models, collaborate on data workflows, and implement MLOps best practices in a fintech environment.

As an Applied AI Engineer at Luminai, you will design experiments, optimize machine learning models, and enhance AI platforms for healthcare automation.

The Forward Deployed Engineer will collaborate with customers to design and deploy AI solutions, enhance workflows, and improve healthcare operations through software engineering and cloud infrastructure.

The Senior Software Engineer will lead application development projects, enhance user-facing applications, and implement best software practices while collaborating on product direction.

Lead and mentor development teams, liaise with clients to translate requirements, own technical delivery and architecture, ensure best practices in DevOps, CI/CD, testing, observability, and cloud operations, and resolve blockers to deliver secure, scalable applications.