Top Python Jobs in Toronto

Build, maintain, and improve highly automated build, release, testing, and continuous delivery infrastructure. Develop internal tools and automation, collaborate with Development, QA, and Operations, and implement AWS-based technologies to scale infrastructure and accelerate testing. Partner with internal customers to roll out projects, monitor adoption, gather feedback, and refine processes. The role requires software development experience, cloud and containerization knowledge, and cross-functional collaboration.

Analyzes investment operations processes, identifies automation opportunities, translates business needs into requirements and future-state designs, and develops or supports solutions using Microsoft Power Platform, Fabric, Power BI, Python, and related tools. The role manages testing, documentation, implementation, production support, controls, governance, stakeholder collaboration, and user education while improving efficiency and reducing operational risk.

Designs, builds, and optimizes scalable data solutions for omnichannel marketing, analytics, and AI products. Responsibilities include developing Python and SQL ETL pipelines, enterprise data warehouses, BI dashboards, system integrations, data models, and AI-enabled solutions. The role gathers requirements from clients and stakeholders, supports Snowflake-based platforms, improves data quality and performance, and establishes reusable engineering practices, documentation, and Git-based workflows.

Leads enterprise QA automation across multiple projects, establishing testing governance, designing Selenium and Robot Framework automation frameworks, and improving test coverage and release readiness. The role combines hands-on automated and manual testing, regression and integration testing, defect management, test strategy development, quality reporting, and team guidance. It partners with development, product, architecture, and business teams to identify risks, improve testing processes, and build sustainable in-house QA capability.

Develops and optimizes credit acquisition strategies, underwriting criteria, credit line assignment rules, and automated decisioning processes. Uses SQL, Python or R, advanced analytics, and machine learning to monitor portfolio performance, delinquency, defaults, and credit exposure. Collaborates with Credit Operations, Product, Engineering, Finance, and Growth teams to implement risk controls, manage exceptions, ensure regulatory compliance, and translate analytical insights into actionable credit policies.

Allocate merchandise to retail stores and counters to maintain optimal inventory levels, support sales, and reduce overstock and stock-outs. Generate allocation and inventory reports, analyze large datasets, identify trends, and collaborate with merchandising, planning, and retail operations teams. The role also requires accurate ERP and inventory data maintenance, strong communication, and flexibility in a team-oriented retail environment.

Lead functional and automated testing for ETL and Data Cloud projects. Develop complex SQL queries, validate data warehouses, and apply QA fundamentals using Azure, Python, and Pandas. Work within Agile teams, take ownership of deliverables, and guide team members toward successful testing outcomes.

Architects and develops AI-powered systems, backend services, APIs, experimentation frameworks, and automation using foundational models. Integrates AI capabilities with microservices, AWS, Snowflake, and diverse technology stacks while ensuring scalability, reliability, and maintainability. Collaborates with product, data science, and engineering teams to translate business needs into technical solutions, evaluate emerging AI tools, and rapidly prototype proof-of-concept applications.

Leads the technical vision and delivery of an enterprise agentic AI program. Oversees architecture, evaluation, deployment, MLOps, reliability, security, and scalability across multiple workstreams. Partners with executives and client stakeholders on roadmaps and high-stakes decisions, aligns data science and engineering teams, establishes technical standards, and mentors senior technical leaders. Requires deep experience in AI/ML, LLMs, agentic systems, AWS, distributed systems, evaluation, and production-scale software engineering.

Leads Kepler’s cross-functional IT Operations team while remaining hands-on with infrastructure, networking, cloud platforms, DevOps, security, incident response, and escalations. Owns operational reliability, technology roadmaps, lifecycle management, documentation, budgeting, vendor coordination, disaster recovery, and security controls. Coaches and develops team members, supports hiring, manages projects and risks, and communicates infrastructure performance and operational priorities to senior leadership.

Lead architecture and hands-on engineering of Pantheons data platform: extend ingest, curation, and retention services; build ML/LLM-ready data infrastructure; mentor engineers; operate in a DevOps model; ensure data governance, observability, reliability, and cross-functional partnership.

Design, build, deploy, and improve AI-enabled tools, automations, integrations, and workflows for customer experience operations. Lead initiatives from discovery through launch and measurement, translate operational processes into system logic, evaluate AI quality, troubleshoot integrations, document solutions, and partner with CX, Product, Engineering, Data, and other teams to improve efficiency and customer outcomes.

Design, develop, launch, and maintain scalable backend systems and APIs used by partners and merchants. Collaborate with engineering teams and stakeholders, balance delivery speed with system quality and reliability, navigate large codebases, debug software, conduct code reviews, and write clear, tested, extensible code using distributed-systems technologies.

Own revenue-focused data science from opportunity sizing through production ML. Investigate and measure product changes, build and operate batch and online ML systems for personalization, experimentation, and automation, and partner cross-functionally to integrate models into user-facing products. Establish monitoring, lineage, reproducibility, and security practices; improve data pipelines; mentor data scientists; and define ML development best practices while using AI tools to accelerate delivery.

Leads the design, implementation, testing, and delivery of embedded firmware for pluggable optical modules. Develops C/C++ and Python firmware, defines requirements and system architecture, analyzes performance, collaborates with hardware, ASIC, and software teams, and supports Agile/Scrum delivery. Mentors junior engineers, improves development workflows and coding standards, and may serve as a Product Owner or technical lead.

Build and maintain cloud infrastructure, APIs, data and inference pipelines, databases, CI/CD systems, monitoring, and Kubernetes deployments for machine learning products. Develop Python backend applications, integrate model registries and MLOps frameworks, monitor model drift and vulnerabilities, optimize Google Cloud infrastructure, and support testing, documentation, code reviews, and AI platform roadmap planning.

Deploy and troubleshoot complex enterprise software integrations for customers using APIs, lightweight code, logs, and AI-powered virtual-agent configurations. Translate requirements into production-ready solutions, develop scripts and proofs of concept, validate AI responses, resolve technical issues, support testing and launches, and collaborate with customers, architects, engineering, product, and support teams. The role also creates reusable integration patterns, documentation, and deployment tooling for future programs.

Operate and improve client infrastructure for availability, efficiency, and visibility. Design and implement automation, monitoring, cloud, and infrastructure solutions; perform maintenance planning, audits, troubleshooting, and multi-system root cause analysis. Advise clients on technology roadmaps, document procedures, mentor teammates, and participate in on-call escalations. The role requires broad cloud, Linux, networking, virtualization, containerization, configuration management, and DevOps expertise.

Hands-on IT Systems Administrator responsible for automating internal workflows, managing end-user hardware and software, supporting Oracle Simphony POS systems, maintaining networks and VPNs across restaurant locations, administering user access, and developing documentation and SOPs. The role also supports data accuracy, reporting, dashboards, and occasional troubleshooting during evenings and weekends. Regular travel to locations across the Greater Toronto Area is required.

Provides technical leadership for cloud platform engineering, including cloud architecture, infrastructure automation, CI/CD, security, reliability, self-service delivery, and developer enablement. The role leads design and code reviews, mentors engineers, improves cloud services and delivery processes, and guides implementation across teams using public cloud platforms, Terraform, Kubernetes, and modern DevOps tooling.

Build and operate critical software for power-campus design, construction, simulation, optimization, equipment integration, and energy management. Own technical areas, shape roadmaps, make architectural decisions, debug production systems, establish data models and interfaces, improve testing and observability, and mentor engineers. The role collaborates across power systems, construction, robotics, and company leadership to deliver reliable software interacting with physical infrastructure.

Research and develop world models that perceive, simulate, and forecast changes in properties and infrastructure. Design representation-learning and predictive-modeling approaches using aerial and satellite imagery, property records, and other signals. Build rigorous evaluations, run large-scale cloud GPU experiments, document findings, and transition successful research into production capabilities. The role requires deep learning expertise, empirical rigor, strong ownership, and collaboration with AI and engineering teams.

Own product and infrastructure security across fintech products and cloud environments. Lead threat modeling, architecture reviews, secure code reviews, vulnerability management, bug bounty operations, CI/CD security scanning, IAM and secrets management, and security standards. Partner directly with engineering leadership to identify and remediate critical vulnerabilities across backend services, APIs, frontends, Solana programs, and infrastructure.

Leads advanced data analytics for Tribal healthcare initiatives, including data resource inventories, quality assessment, linkage analysis, predictive and prescriptive modeling, reporting, dashboards, and large-scale analytics projects. Establishes data quality frameworks, supports federal compliance, coordinates cross-functional initiatives, and mentors junior analysts. Uses Python, R, SQL, statistical methods, machine learning, and data modeling to produce actionable insights and maintain data integrity.

Designs and maintains data models, AI solutions, marketing automation architectures, and governance frameworks that support segmentation, targeting, and go-to-market efficiency. Advises marketing teams on data-driven strategies, builds MCP servers and LLM-based solutions, develops innovation roadmaps, and partners cross-functionally on adoption. The role also mentors team members and requires production-quality Python, API development, marketing automation, analytics, and modern cloud deployment experience.