Top Python Jobs in Toronto

Design, build, and deploy enterprise-scale agentic AI and generative AI solutions for banking. Develop full-stack LLM applications, integrate multiple model providers, establish evaluation and feedback systems, and prototype emerging AI technologies. Work in agile squads using MVP-driven delivery while ensuring security, resiliency, scalability, and regulatory alignment. Mentor junior engineers and collaborate cross-functionally on production-grade AI capabilities.

Develop scalable business intelligence and reporting solutions across marketing, loyalty, merchandising, and promotional initiatives. Responsibilities include integrating enterprise data, building automated pipelines, creating dimensional and semantic models, developing Power BI dashboards and DAX calculations, analyzing business performance, ensuring data quality, and communicating insights to stakeholders. The role requires strong SQL, Power BI, data modeling, Python or PySpark, and cloud analytics experience.

Provides business intelligence, reporting, analytics, and strategic insights for wealth management stakeholders. Builds reporting solutions, interprets and visualizes data, identifies growth opportunities, manages requirements and stakeholder relationships, and translates complex analysis into actionable business recommendations. The role also develops reporting commentary, educates partners on data-driven decision-making, and manages project scope and timelines.

Manages stress testing analytics, enterprise reporting, and risk data initiatives. Aggregates, maps, reconciles, validates, and analyzes large datasets; consolidates model results; applies analytical adjustments; and transforms complex outputs into visualizations and presentations for senior stakeholders. The role supports credit risk, loss forecasting, lending products, and stress testing while using Power BI, Excel, and PowerPoint, with potential Python, SQL, and SAS applications. It also provides analytical support, recommendations, and data-driven insights across technical and business teams.

Leads the long-term technical health of Carta’s Investors business unit by solving ambiguous, complex problems; driving architectural improvements for scalability and reliability; aligning teams on technical decisions; defining safe AI engineering practices; and mentoring senior engineers. The role focuses on distributed systems supporting fund financials, tax and compliance, LP management, and reporting.

Leads technically complex software projects from concept through production, improving system performance, reliability, and simplicity. Mentors engineers through code reviews and architectural guidance, collaborates with product and design, and applies modern AI-assisted engineering tools. The role supports Carta’s Investors platform, including fund financials, tax and compliance, LP management, reporting, ledgers, reconciliations, and capital calls.

Designs, builds, and maintains scalable data platforms, architectures, and pipelines using Microsoft Fabric, Databricks, and Snowflake. Responsibilities include data modeling, ETL/ELT, workflow optimization, security and compliance, data quality improvements, and collaboration with analysts, scientists, engineers, and business stakeholders.

Leads end-to-end analytics initiatives, including stakeholder discovery, data validation, dashboard and reporting design, deep-dive analysis, KPI development, experimentation, and executive presentations. Collaborates with data engineers on modeling and reporting quality, establishes analytics standards and governance, mentors junior analysts, and translates complex business questions into actionable recommendations.

Supports client analytics engagements by analyzing data, building dashboards and recurring reports, tracking KPIs, validating data quality, documenting metrics, and communicating insights. Collaborates with engineers, analysts, product managers, designers, and stakeholders to translate business questions into analytical requirements and improve reporting workflows. The role also provides exposure to consulting, digital product development, AI, UX, and data governance.

Develop and deploy production-ready AI and machine learning models across analytics projects, using statistical modeling, NLP, forecasting, optimization, and advanced ML techniques. The role includes experimentation, data analysis, visualization, storytelling, lifecycle management, and collaboration with engineering and MLOps teams. Candidates will work with cloud and high-performance computing platforms to deliver AI data products in an agile environment.

Leads end-user support and experience for business application systems, overseeing second-line production support, knowledge management, change readiness, JIRA triage, KPI reporting, workflow optimization, and self-service enablement. Partners with Risk Management, Technology, and vendors to support the eGRC platform, manage production issues, coordinate system changes, and facilitate testing. The role provides operational leadership, improves support efficiency, and ensures scalable, consistent service outcomes.

Leads full-stack application and microservices design, development, implementation, and support across Power Platform and Azure technologies. Translates business requirements into scalable system designs, integrations, interfaces, and processing logic. Develops technology roadmaps, leads complex solutions, facilitates design reviews, advises senior stakeholders, and mentors junior developers. The role requires technical leadership, technology selection, and collaboration across project and engineering teams.

Build and maintain backend Go services for Stream’s AI moderation product, including APIs, data models, integrations, reliability improvements, refactoring, testing, and performance optimization. Participate in on-call, troubleshoot production issues, work directly with customers, and contribute React changes when features span the stack.

Develop scalable business intelligence and reporting solutions across marketing, loyalty, merchandising, and promotional initiatives. Responsibilities include integrating enterprise data, building automated pipelines and analytical datasets, designing dimensional and semantic models, creating Power BI dashboards and advanced DAX calculations, analyzing business performance, ensuring data quality, and communicating insights to stakeholders. The role requires strong SQL, Power BI, data modeling, cloud analytics, and stakeholder communication skills.

Develop and productionize NLP and AI features for multilingual communications risk and compliance analysis. Design, fine-tune, evaluate, serve, and monitor transformer and LLM-based models, including RAG and embedding search. Own database architecture, data models, administration standards, testing, and infrastructure improvements supporting NLP pipelines. Collaborate with research, product, MLOps, engineering, and revenue teams; explain model behavior to clients and mentor engineers.

Develop and productionize NLP and LLM solutions for multilingual financial communications, including model training, fine-tuning, evaluation, RAG, and risk detection. Design and administer databases and data models supporting NLP pipelines, improve cloud infrastructure, document technical work, explain model behavior to clients, collaborate across research, product, MLOps, and engineering teams, and mentor engineers.

Supports FANUC robot applications integrating physical AI platforms, motion planning, simulation, camera sensors, digital twins, and related hardware and software. Responsibilities include coding, testing, troubleshooting, demonstrations, configuration, technical customer support, supplier evaluation, project coordination, and software release trials. The role collaborates with customers, integrators, sales, service, and project teams, with occasional travel to customer and integrator sites.

Leads strategic product management and digital transformation for enterprise lending, client portal, and debt capital markets platforms. Owns product roadmaps, agile delivery, platform integration, AI/ML initiatives, prototypes, governance, and regulatory alignment. Partners with senior stakeholders, engineers, designers, operations, risk teams, bankers, and corporate clients to deliver unified lending workflows and self-service digital experiences.

Design, build, and deploy enterprise-scale agentic AI and generative AI solutions for banking. Develop full-stack LLM applications, integrate multiple model providers, establish evaluation and feedback systems, and research emerging autonomous AI technologies. The role emphasizes rapid MVP delivery, production reliability, security, and scalable architectures. It also requires cross-functional collaboration, technical mentorship, and alignment with regulated financial-services requirements.

Supports enterprise data platforms, ETL processes, reporting environments, and data integration initiatives. Responsibilities include monitoring data loads, troubleshooting database and reporting issues, developing SQL queries and procedures, validating data, creating Power BI dashboards, supporting Snowflake and Microsoft data platforms, and contributing to data governance, migration, automation, and quality improvements.

Design, build, automate, optimize, and support complex cloud data pipelines and ETL/ELT processes. Develop unified Databricks data platforms, data lakes, lakehouses, warehouses, and dimensional models. Integrate and migrate data across Oracle, Azure, Databricks, and Microsoft Fabric. Create Azure Data Factory pipelines, implement CI/CD and DataOps practices, and perform performance tuning, monitoring, troubleshooting, and data provisioning for large-scale enterprise environments.

Develop and maintain large-scale, fault-tolerant software systems for Lyft’s GovTech team. Responsibilities include partner integrations, roadmap and architecture planning, writing tested and maintainable code, leading projects, collaborating cross-functionally, supporting internal and external partners, participating in code reviews, and promoting engineering best practices. The role involves distributed systems, cloud platforms, databases, regulatory integrations, and potentially machine learning or LLM applications.

Supports reporting production, data analysis, and analytics operations across the COR.IQ product portfolio. Develops and maintains SQL and Qlik queries, data extracts, scripts, and reporting enhancements; investigates data quality issues and operational anomalies; supports product onboarding and client requests; and provides backup coverage for the Data Analyst 3. The role also develops expertise in fraud analytics, reporting systems, product operations, and continuous improvement.

Develop and productionize NLP and AI solutions for multilingual communications data, including LLM and transformer-based models. Design databases, data models, administration standards, and evaluation systems supporting NLP pipelines. Deploy and monitor models and data systems on cloud platforms, improve infrastructure, document technical findings, advise product and engineering teams, explain model behavior to clients, and mentor engineers.

Partners with business functions to advise on and build AI-powered solutions using Microsoft Copilot Studio, Claude, and low-code platforms. Translates requirements into solution designs, manages testing and deployment, develops reusable prompts and agents, evaluates proofs of concept, and supports AI adoption. Ensures solutions meet security, privacy, regulatory, and responsible AI requirements while collaborating with enterprise AI and learning teams.