Top Python Jobs in Toronto

The Director of FP&A - Operations will partner with operations leaders to manage P&L, build financial models, and automate reporting using AI tools.

Design, develop, and maintain full-stack banking applications using Java, Angular, TypeScript, Node.js, and Python. Integrate and optimize Java-based REST APIs, write automated unit tests (JUnit 5), collaborate with clients and cross-functional teams, participate in code reviews and Agile delivery, and contribute to CI and quality practices to deliver scalable production solutions.

Design, implement, and maintain scalable backend systems for campaign creation, targeting, content assembly, scheduling, and handoff to delivery. Ensure reliability, observability, and operational excellence; own features end-to-end, mentor junior engineers, and drive extensible, fault-tolerant distributed architectures.

Build and own core components of an LLM-powered agent platform: orchestration, tool integrations, APIs, knowledge/memory infrastructure, trust & safety, and evaluation tooling. Partner with Operations to translate workflows into agent capabilities, mentor teammates, and ship production-ready, scalable AI-native systems.

Architect and build a full-stack platform spanning React frontends and Node.js backends. Lead technical decisions, design and optimize GraphQL/REST APIs and databases, improve observability, implement testing strategies, mentor engineers, introduce new technologies, and drive cross-team technical initiatives to deliver scalable, reliable software.

Lead the FinOps engineering team to design and implement backend services, cost-optimization tooling, data pipelines, APIs and dashboards, mentor engineers, and partner across engineering, finance, and product to drive cloud and vendor cost efficiency.

Lead the evolution of the recommendations engine system into a scalable distributed architecture, ensuring production stability and performance while mentoring engineers and collaborating with ML teams.

The role involves helping modernize industries through IoT solutions, engaging with clients, managing implementations, and driving tech adoption. Significant pre-sales experience is required, coupled with a strong technical background in hardware and cloud applications.

The Senior Software Engineer will design and develop scalable systems for a cloud-based SaaS platform, lead technical discussions, and ensure high-quality code delivery.

The Data Engineer will develop and maintain data pipelines, ensure data quality, and collaborate with business teams to implement insightful data solutions.

Embedded product-oriented data specialist supporting Identity product teams. Designs analyses and experiments, analyzes complex datasets, builds pipelines and repeatable reporting, and delivers data-driven recommendations to inform product and engineering decisions focused on fraud, data enrichment, and cost optimization.

Own, build, and optimize Spark-based production data pipelines and ML data lake on GCP Dataproc to support recommender systems. Collaborate with ML engineers, resolve performance bottlenecks, and deliver scalable, reliable data products for AI-driven personalization.

The Senior Data Engineer will design and maintain streaming data pipelines, develop analytical databases, and ensure data system reliability while collaborating with teams across the organization.

Lead design and build scalable data architectures, ETL pipelines, ingestion and data quality frameworks. Collaborate with cross-functional teams, enforce data governance, analyze data for insights, mentor junior engineers, and serve as the technical authority on data engineering best practices.

Senior Sales Engineer supporting pre-sales for Mastercard Identity in North America. Act as product expert to qualify prospects, design technical solutions, run proofs of value, provide training, create documentation, present at events, and relay customer feedback to Product. Leverage data science and machine learning knowledge, API/web architecture expertise, Python and SQL skills, and strong communication to drive sales and ensure smooth onboarding.

Work as an AI-focused intern to develop, train, validate, and deploy machine learning and computer-vision models (YOLO, Python, OpenCV, TensorFlow/PyTorch) for production-floor systems. Collaborate with cross-functional teams to gather requirements, monitor and improve model performance, document methods, report progress, and provide training and support for AI initiatives.

Develop and maintain cloud-based IoT applications for manufacturing. Design secure, scalable full-stack solutions, APIs, data integrations and pipelines. Collaborate with architects, product owners, developers, and stakeholders; follow DevOps and agile practices; mentor team members and troubleshoot production issues.

Test and validate AI models and software for automotive use cases: generate ground truth, build annotated datasets and testing frameworks, evaluate technologies, support R&D engineers, coordinate projects and outsourced work, and collaborate with internal and external partners to drive innovation and product readiness.

Design, build, and maintain scalable data pipelines and storage (data lakes/warehouses). Integrate diverse sources, enforce data quality, security and compliance, optimize ETL/ELT, monitor pipelines, and mentor junior engineers while collaborating with data scientists, analysts, and stakeholders.

The Product Security Engineer will implement security testing, manage vulnerabilities in codebases, and integrate security practices into CI/CD pipelines while collaborating with engineering teams.

Lead architecture and scaling of finance technology across Accounting, Tax, Treasury, Procurement, and FP&A. Design data models and integrations for Oracle Fusion, build SQL/PLSQL-based integrations and web services, embed AI-assisted development, automate financial workflows, and translate accounting requirements into scalable technical designs and documentation.

The Senior Developer Experience Engineer will own CI/CD infrastructure and internal tools, improve developer productivity, and foster team collaboration through effective tooling and automation.

Lead the design, modeling, simulation, and live tuning of the Zynga Poker in-game economy. Drive retention and monetization through data-informed economy features, A/B testing, predictive models, and cross-functional collaboration with product, analytics, and live-ops teams.

Support deployment, training, and support of internal SoC design and verification flows. Work with project engineers and methodology developers to ensure front-end and back-end flows function correctly, ramp teams, liaise with EDA vendors to resolve tooling issues, and identify efficiency improvements across engineering projects.

Lead the design and development of machine learning models, collaborating with teams to optimize solutions and mentor junior members while ensuring technical excellence.