Top Python Jobs in Toronto

Investigate and resolve technical customer issues across web applications, accounts, data, integrations, APIs, and authentication. Reproduce problems, analyze logs and database records, document solutions, escalate defects, validate fixes, support incidents, and improve troubleshooting processes. The role also involves maintaining support documentation, identifying recurring issues, building lightweight automation tools, establishing escalation procedures, and protecting customer data.

Deploys, installs, tunes, monitors, and supports autonomous mobile robotics solutions at manufacturing sites. Troubleshoots robotics, networking, and security issues; validates deployment milestones; supports customers; documents field activities; and trains internal teams and customers. Collaborates with installation contractors, product development, engineering, and operations teams. The role is hands-on, customer-facing, field-based, and requires extensive travel across North America and potentially Europe.

Develop and maintain applications, backend systems, APIs, and platform features incorporating AI components. Use Python, SQL, prompt engineering, and context engineering to build and optimize solutions. Integrate AI into software and knowledge systems, manage data access and security, monitor performance and model costs, and support compliance. Collaborate with analysts, developers, and stakeholders while managing multiple priorities and communicating technical progress.

Develop analytical solutions, enterprise dashboards, reports, and data visualizations for Small Business Banking stakeholders. Partner with data engineering and technology teams to define data requirements, business rules, quality standards, and enhancements. Use Power BI, Tableau, Python, PySpark, Databricks, and Azure to support self-service insights and data preparation. Maintain governance documentation and controls while delivering accurate results in a fast-paced environment.

Investigates suspected fraud, analyzes transactional activity and fraud trends, optimizes detection rules, assesses risks and control gaps, and prepares dashboards and reports. The role supports fraud prevention initiatives, control testing, process automation, and strategic transformation projects while collaborating with Operations, Risk, Compliance, Product, and Technology teams. It also serves as a subject matter expert and mentor for junior analysts.

Lead architecture and delivery of scalable Maps Search systems, including backend services, retrieval, autocomplete, recommendations, data pipelines, and ML serving infrastructure. Improve latency, reliability, relevance, observability, and operational health for high-throughput services. Set technical direction across teams, make system-level tradeoffs, mentor engineers, and collaborate with product, machine learning, science, mobile, and infrastructure partners.

Build and ship full-stack features for an LLM-powered conversational AI assistant. Own backend services, APIs, data models, React interfaces, streaming experiences, agentic workflows, observability, and evaluation. Design recovery and human handoff experiences, troubleshoot production issues, mentor engineers, contribute to technical reviews, and collaborate with product and design teams. The role requires strong software engineering fundamentals and hands-on experience delivering conversational AI products used by real customers.

Build and operate infrastructure supporting AI model training, inference, and product platforms. Responsibilities include managing Kubernetes and GPU clusters across cloud and on-premises environments, provisioning compute and networking, operating databases and Kafka, developing Python-based automation and self-service tooling, and leading cloud migrations and platform improvements focused on reliability, security, and cost efficiency.

Designs enterprise cloud architecture and infrastructure across Azure and GCP, leads Kubernetes platform engineering, builds CI/CD and GitOps automation, and implements infrastructure as code with Terraform. Establishes security, governance, compliance, observability, and cost-optimization frameworks. Leads cloud migrations and multi-region deployments while mentoring engineering teams, driving DevOps transformation, overseeing architecture reviews, and shaping technology roadmaps.

Build and improve full-stack web and mobile workflows for MaintainX’s maintenance platform. Ship features end to end, shape architecture and product roadmaps, own feature reliability and performance, review code, mentor developers, and improve testing and delivery practices. Work with TypeScript, React, Node.js, and MySQL while addressing large datasets, responsive interfaces, offline behavior, and multi-site scalability.

Leads applications development teams and oversees enterprise software delivery, technical strategy, staffing, risk, and compliance. Designs and deploys scalable AI agents, data-intensive ELT/ETL pipelines, microservices, data federation layers, and cloud-native integrations. Uses Python, PySpark, Databricks, Kafka, Kubernetes, OpenShift, Google ADK, LLMs, and agentic AI tools to automate workflows, support human-in-the-loop processes, and improve data engineering practices, quality, security, and operational efficiency.

Supports Stantec’s annual SR&ED claim development cycle by planning activities, documenting project information, tracking claims, organizing supporting records, assisting with cost estimates, and monitoring deadlines. The intern collaborates with research advisors and managers while learning about engineering and scientific innovation projects and government research funding. The role requires strong organization, communication, teamwork, Python proficiency, and enrollment in a science or engineering university program.

Design, build, and operate Sentry’s streaming platform, including Kafka infrastructure, streaming runtimes, developer APIs, and control-plane automation. Develop resilient, high-throughput real-time processing systems with strong correctness guarantees. Improve scalability, observability, monitoring, failover, and operational efficiency while partnering with product engineers to support reliable ingestion pipelines.

Design, develop, and improve scalable software for an investment platform. Lead software development across the lifecycle, mentor junior engineers, solve complex technical problems, maintain code quality through testing and reviews, and recommend technology enhancements. The role is remote in the USA with four in-person retreats annually.

Develops and maintains Java applications and RESTful APIs across the software development lifecycle. Translates business requirements into technical specifications, designs and implements secure software, performs testing and troubleshooting, manages releases and version control, and supports system design. The role also evaluates technologies, applies application security and performance standards, and works with databases, CI/CD pipelines, automation, monitoring, and cloud technologies in an enterprise banking environment.

Lead design and delivery of scalable, governed data ingestion and integration pipelines for structured, semi-structured, and multimodal data to enable AI, ML, and Generative AI. Partner with product, data science, architecture, risk, and operations to define requirements, ensure data quality, lineage, security, and observability, and evaluate new technologies. Mentor engineers, drive cross-functional initiatives, improve platform resilience, and measure ingestion and AI data effectiveness.

Leads Developer Experience and SDLC modernization across the organization. Designs internal developer platforms, agentic automation, cloud infrastructure, CI/CD pipelines, quality gates, and secure DevSecOps workflows. Partners with architecture, security, and product teams to improve engineering productivity and tool adoption. Provides technical leadership, mentorship, documentation, architectural guidance, and hands-on development using Python or Java and modern cloud-native technologies.

Develop and maintain embedded firmware for IoT water infrastructure products. Responsibilities include architecture input, detailed implementation, unit testing, documentation, code reviews, hardware-assisted debugging, BSP and chip-driver development, production troubleshooting, QA support, and field-release maintenance. The role collaborates with multidisciplinary engineering teams, uses lab equipment and AI-assisted development tools, and participates in Agile processes.

Develop and maintain full-stack coaching applications across web and mobile platforms. Build React frontends, Python and AWS-backed APIs, and support React Native iOS applications. Apply testing, automation, DevOps, security, documentation, and AI-assisted development practices. Collaborate with infrastructure and engineering teams on integrations, technical planning, sizing, and project delivery from requirements through launch.

Build end-to-end internal products and tooling for robotics dataset delivery, including review and QA interfaces, dashboards, data viewers, export and validation logic, pipelines, APIs, and data infrastructure. Convert manual workflows into reliable tools, take ambiguous problems from concept to shipped v1, and iterate with users. The role spans front-end, backend, data systems, and product development, supporting petabyte-scale video and sensor datasets used by AI labs and robotics companies.

Develop and productionize retail demand forecasting and inventory optimization models using LightGBM, CatBoost, Python, and PySpark. Build Databricks-native training, inference, monitoring, and MLOps workflows with MLflow. Establish data validation, observability, testing, CI/CD, and reliable operational pipelines while partnering with Product and Data Engineering. Preferred experience includes supply chain optimization, Databricks advanced features, explainable AI, and CI/CD automation.

Leads a team developing Triton compiler technologies for Intel GPUs and AI accelerators. Responsibilities include compiler design and optimization, project delivery, cross-functional collaboration, software quality, performance analysis, open-source contributions, hiring, mentoring, and career development. The role requires technical leadership in compiler technologies, AI/ML workloads, GPU architectures, and software engineering practices.

Build and maintain scalable data pipelines, data platforms, reporting infrastructure, reconciliation systems, and self-service analytics tools. Develop customer-facing and internal applications, integrate internal and external data sources, optimize near-real-time processing, ensure data quality and auditability, and evaluate emerging technologies. Collaborate with engineering, product, analytics, security, and data science teams while participating in on-call support.

Provides day-to-day application and system support, investigates and resolves production issues, performs basic problem determination, analyzes logs, monitors applications and batch processes, and supports Java APIs, cloud services, UNIX/Linux, and mainframe environments. The role requires incident management, stakeholder communication, knowledge transfer, productivity improvement, rotating shifts across seven days, and onsite work four days per week.

Performs operational analysis and validation of FRTB production runs supporting trading desk market risk requirements. Analyzes market risk trends, drivers, data quality, and regulatory reporting; identifies and resolves issues; maintains procedures, controls, governance, and data lineage; and supports audits, stakeholder requests, projects, and risk infrastructure initiatives.