Top Python Jobs in Toronto

Perform actuarial analyses, research, validations, and financial projections for P&C insurance. Develop monitoring reports, dashboards, and KPIs; collaborate with claims, legal, and operations; document actuarial conclusions; lead moderately complex projects; provide subject-matter expertise, mentorship, and process improvements while ensuring regulatory and risk control compliance.

Own the technical direction and multi-year strategy for a modeling platform spanning backend APIs, SDKs, frontend components, and AI interfaces. Build self-service framework capabilities, make platform architecture decisions, align cross-functional and product engineering teams, partner on computation-engine architecture, and coach engineers toward senior and staff-level impact.

Full-time interns will learn capital markets, Foreign Exchange or Fixed Income products, trading workflows, valuation, risk management, and the MX.3 platform. They will analyze business requirements, configure and test solutions, validate trading and risk workflows, investigate client issues, support implementation and client projects, and communicate findings to technical and business stakeholders. The role combines finance, quantitative analysis, technology, and functional consulting in a hybrid Toronto office environment.

Research and develop advanced networking technologies and protocols for AI infrastructure, cloud, and data-center networks. The role involves designing technical roadmaps, optimizing network performance, addressing distributed systems challenges, and deploying innovations involving RDMA, routing, congestion control, topology design, and resource allocation. The researcher will also collaborate with academic and industry professionals and connect technical research with product strategies.

Research and develop an open-source agent framework, including architecture, abstractions, tooling, developer experience, self-evolution, and multi-agent collaboration. Analyze emerging agent projects such as OpenClaw and Hermes, integrate effective innovations, and deploy the framework in business and consumer products. Gather developer and product feedback to improve the framework. The role requires Python expertise, LLM knowledge, and familiarity with agent frameworks.

Build and operate a reliable ML platform for large-scale distributed GPU training. Responsibilities include Kubernetes infrastructure, developer-facing CLIs and SDKs, AWS infrastructure, data and artifact management, experiment tracking, model registries, CI/CD, observability, documentation, security guardrails, and platform adoption. The role partners closely with researchers and engineers to improve training speed, reliability, usability, and cost efficiency for autonomous transportation systems.

Develop and deploy production machine learning solutions for retail personalization and loyalty programs. Responsibilities include recommender systems, ranking models, offline evaluation, large-scale PySpark feature engineering, ML platform design, cloud training pipelines, agentic AI solutions, workflow orchestration, and production reliability. The role also involves technical leadership through code reviews, documentation, mentorship, and communication of technical and business concepts.

Build and operate technical systems, automations, data pipelines, and AI-powered workflows supporting go-to-market teams. Responsibilities include signal-based outbound prospecting, lead-data cleaning and enrichment, Salesforce synchronization, lead scoring, lead routing, pipeline generation, and integrating AI into revenue workflows. The role partners with Sales and Marketing and requires hands-on ownership of scalable solutions in a SaaS environment. It is a flexible hybrid position based in Toronto.

Directs credit trading activities across US and Canadian markets, executing transactions, supporting order management, and providing market insights to investment teams. The role manages counterparty relationships, coordinates with Legal, Accounting, Operations, and Compliance, supports pre- and post-trade analytics and transaction cost analysis, and develops junior traders. Candidates need at least seven years of credit trading experience, knowledge of multiple asset classes and trading platforms, and strong communication and analytical skills.

Soutient la documentation réseau dans NetBox, les projets de renouvellement LAN, le déploiement d’équipements et la gestion des stocks. Rédige des comptes rendus, suit les actions et fournit un soutien administratif et documentaire. Le poste exige des bases en réseaux TCP/IP, scripting, équipements réseau, organisation et communication, ainsi qu’une capacité à déplacer occasionnellement du matériel et à voyager à Montréal selon les besoins.

Develop and deploy production machine learning solutions for retail personalization and loyalty offers. Build recommender and ranking models, large-scale PySpark feature pipelines, offline evaluation frameworks, ML platform infrastructure, and agentic AI systems. Operate cloud training workflows and analytical pipelines while improving reliability, scalability, and engineering standards through mentorship and code review.

Designs, develops, and deploys production-grade AI and generative AI solutions in enterprise cloud environments. Responsibilities include building NLP, LLM, predictive modeling, and intelligent-agent applications; integrating AWS Bedrock and SageMaker; designing APIs and microservices; managing model lifecycle, security, monitoring, and costs; and providing technical leadership, code reviews, and mentorship.

Designs and delivers scalable Global Transaction Banking data and platform solutions. Provides technical leadership for architectures, engineering standards, roadmaps, resilience, reliability, and platform adoption. Builds distributed, event-driven, big-data systems and APIs while managing technical debt, DevOps practices, and cloud environments. Partners with engineering, product, and business stakeholders, communicates complex concepts, estimates delivery efforts, and promotes Agile, customer-centric engineering culture.

Own end-to-end delivery programs for robotics and embodied AI datasets. Coordinate Sales, Data Operations, Labeling, and Engineering to meet customer specifications, volumes, quality standards, and timelines. Build scripts, QA checks, packaging tools, manifests, dashboards, and reporting to automate delivery workflows. Define dataset standards, monitor metrics, manage escalations, and serve as a senior customer-facing delivery lead for AI-lab accounts.

Conduct advanced application security research across GitLab’s DevSecOps and AI-powered platforms. Identify and exploit novel, systemic, and chained vulnerabilities; develop proof-of-concept exploits, testing methodologies, and research automation; assess AI attack vectors and open-source dependencies; drive remediation and security improvements; advise engineering teams, contribute to roadmaps, mentor researchers, and share findings with the security community.

Conducts advanced application security research across GitLab’s DevSecOps and AI-powered platforms. Responsibilities include discovering and exploiting systemic vulnerabilities, penetration testing, developing proof-of-concept exploits, researching AI and agentic security threats, building automated research tooling, coordinating remediation, mentoring security professionals, and communicating findings to engineering and security communities.

Leads power-system modeling and resource interconnection studies for renewable and conventional generation, including power flow, transient stability, short-circuit, EMT, harmonics, and techno-economic analyses. Develops models and automation scripts, guides engineers, serves as a grid reliability or energy-market subject matter expert, supports ISO/RTO stakeholder engagement, contributes to research and innovation, and helps develop client relationships, proposals, and commercial projects.

Leads credit underwriting and valuation analysis, develops and tests strategies, and presents recommendations to senior leadership. Oversees complex analytical work, guides junior analysts, establishes team roadmaps, and monitors strategy performance. Uses SQL, Python, spreadsheets, Tableau, and QuickSight to analyze data and automate reporting. The role includes developing a high-performing analyst team and is expected to evolve into people leadership.

Build and operate Databricks-based data products and pipelines that create, model, and deliver syndicated and custom consumer audience segments. Develop tables, views, jobs, workflows, and real-time processing solutions using Python, SQL, Spark, and Delta Lake. Support marketplace delivery, reporting, observability, metadata, testing, CI/CD, privacy compliance, and AI-assisted development. Partner with data science and commercial teams to translate business requirements into scalable engineering solutions, while promoting architecture and engineering best practices.

Deliver technical presentations, demonstrations, and guidance for Tufin’s network security policy management solutions. Assess prospective customers’ technical needs, support sales activities, advise clients and partners, provide product training, collaborate with product and engineering teams on requirements, and represent Tufin at events. The role requires technical sales or solutions engineering experience, networking knowledge, scripting familiarity, cloud security aptitude, strong communication skills, and French and English fluency.

Lead instrument risk modelling for derivatives, hedge funds, liabilities and other securities. Build tools, validate models, collaborate with traders, finance and developers, and deliver risk reporting and advanced risk-management approaches.

Designs, enhances, supports, and troubleshoots enterprise Identity and Access Management platforms and federation services. The role develops IAM roadmaps, creates secure and compliant solutions, evaluates vendors, provides application-team consultation, resolves escalated issues, maintains technical documentation, and trains junior engineers. Collaboration spans security engineering, architecture, operations, project management, and application teams.

Lead technical strategy and pre-sales engagement for major financial services and insurance accounts. Guide enterprise customers through data and AI transformation, drive Databricks adoption, build technical champions, present solutions to executives, and coordinate sales and technical teams. Apply expertise in big data, data science, cloud platforms, machine learning, and production programming to deliver business outcomes across large global accounts.

Develop and productionize fraud detection machine learning models using large-scale behavioral, device, network, and transaction data. Lead investigations into complex fraud attacks, reconstruct attacker behavior, identify trends, and produce technical reports and customer-facing insights. Collaborate with product, engineering, operations, legal, executives, and customers to improve detection systems and automate analytic workflows.

Lead the technical direction and hands-on development of a real-time fraud detection platform, including streaming, storage, distributed systems, machine learning training pipelines, and AI-assisted engineering tools. The role drives architecture, technical planning, operational health, incident prevention, production support, and collaboration with Product and customer-facing teams. It also mentors engineers, establishes AI-assisted development standards, and evaluates LLM- and agent-based tools for engineering operations.