Top Python Jobs in Toronto

Own end-to-end analytics for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; surface actionable insights; and influence stakeholders’ decisions. The role requires independent data work, strong analytical judgment, clear communication, and ownership of ambiguous, high-impact initiatives.

Provides technical Workday integration consulting to customers after go-live. Responsibilities include researching customer questions, troubleshooting and optimizing configurations, delivering demonstrations, presentations, workshops, feature adoption guidance, configuration reviews, integration optimization, and feature deployments. The consultant serves as a trusted Workday advisor, maintains certifications and product expertise, supports customer decision-making, and helps create programs that improve feature adoption. Travel may be required up to 20%.

The Senior Research Engineer will develop and deliver scalable ML solutions, collaborate with teams, and apply innovative technologies in AI to impact professionals in legal and accounting fields.

Lead backend and AI orchestration systems for CoCounsel Audit: design and operate scalable, low-latency AI workflows, integrate LLMs and retrieval systems, mentor engineers, set platform strategy, and ensure reliability, observability, and auditability at production scale.

Build and maintain large-scale automated testing frameworks, libraries, infrastructure, and test suites for enterprise SaaS applications, APIs, services, and distributed systems. Integrate automation with CI/CD pipelines, leverage AI coding tools, troubleshoot application and production issues, analyze codebases, and expand test coverage. Collaborate with engineering, DevOps, product, and QA teams to improve reliability, observability, performance, and maintainability.

Defines test strategies and performance quality gates while automating testing, deployment, rollback, and validation for scalable virtualized server platforms. Develops unit, integration, and end-to-end test frameworks; creates test plans for microservices; troubleshoots deployment issues; writes deployment scripts; and collaborates with engineering teams on integration testing and environment improvements.

Conduct autonomous hardware and software penetration tests of IoT, embedded, ICS/OT, and automotive systems. Extract and analyze firmware, reverse engineer binaries, assess wireless, vehicle, industrial, network, cloud, and mobile attack surfaces, and review source code and SBOMs. Produce CVSS-rated reports with remediation guidance and VEX justifications, support customer briefings, and contribute to security tooling, research, methodologies, and platform improvements.

Conduct autonomous hardware and software penetration tests of IoT, embedded, ICS/OT, and automotive systems. Extract and analyze firmware, assess wireless, vehicle, industrial, network, cloud, and mobile attack surfaces, review source code and SBOMs, identify and validate vulnerabilities, and produce customer-facing reports with CVSS ratings, VEX justifications, and remediation guidance. Support scoping, debriefs, peer reviews, methodology improvements, tooling, research, and platform enhancements.

Conduct autonomous hardware and software penetration tests of IoT, embedded, ICS/OT, and automotive systems. Extract and reverse-engineer firmware, assess wireless, vehicle, industrial, network, cloud, and mobile attack surfaces, review source code and software components, and identify exploitable vulnerabilities. Produce CVSS-scored reports with remediation guidance and VEX justifications, lead customer debriefs, peer-review deliverables, and contribute to security tooling, research, and platform improvements.

Designs and delivers end-to-end automation solutions for Lilly’s global Finance organization. Responsibilities include assessing opportunities, developing and testing software, creating architecture and test documentation, supporting UAT and integrations, troubleshooting production issues, resolving defects, and assisting with QA, audits, migrations, and risk mitigation. The role uses Python, PySpark, TypeScript, PostgreSQL, AWS, Microsoft Fabric, SAP, and other APIs, while collaborating with finance, technology, analyst, and business teams.

Provides senior-level technical support to enterprise customers by reproducing and debugging complex issues, resolving high-severity incidents, and communicating solutions. Collaborates with Product, Customer Success, and Account Management, leads customer debugging calls, identifies product feedback, documents support activity, mentors team members, improves workflows, contributes to technical documentation, and participates in an on-call rotation.

Lead development and evolution of AlphaSense's financial data taxonomy and generation rules. Serve as subject-matter expert, align cross-functional teams, define requirements for new datasets, ensure AI/LLM compatibility, maintain documentation, and build scalable frameworks to expand and maintain high-quality structured financial data for capital markets users.

Leads a cloud platform engineering team responsible for cloud architecture, standards, automation, security, reliability, availability, and performance. Partners with architecture, risk, security, and application teams to deliver resilient cloud services and platform capabilities. Oversees cloud infrastructure enhancements, controls, observability, and operational excellence while managing staff development, hiring, performance, and technical strategy.

Provide technical support to eCommerce and enterprise customers through chat, email, and video calls. Diagnose issues using logs, system files, remote access, and operating system expertise; recreate and track software defects; document resolutions; meet service levels; collaborate across teams; and participate in an on-call rotation for critical incidents.

Owns and improves the end-to-end software release system across engineering. Responsibilities include managing release calendars, branching strategies, code freezes, readiness checkpoints, deployment coordination, risks, dependencies, stakeholder communications, release governance, and post-release follow-up. The role partners with DevOps and engineering teams to improve CI/CD pipelines, build stability, deployment reliability, automation, and release cadence in a cloud-based SaaS environment.

Own production reliability and infrastructure operations for the GrayKey cloud platform. Responsibilities include AWS monitoring, incident response, vulnerability remediation, networking, IAM and Okta administration, EKS and Argo CD operations, backups, recovery testing, Terraform changes, cost optimization, automation, documentation, and compliance support. The role requires independent work during Pacific and Mountain time-zone hours and involves less than 5% travel.

Supervise daily manufacturing, logistics, inventory, and container-reconditioning operations while ensuring safety, quality, regulatory compliance, and efficiency. Lead production teams, scheduling, traceability, shipping documentation, hazardous-material handling, audits, staff training, and continuous improvement. Maintain operational databases, chemical inventory systems, automated workflows, reporting, and documentation controls. Coordinate maintenance and regulatory inspections while monitoring incidents, corrective actions, and environmental, health, and safety compliance.

Designs, automates, and operates self-hosted Linux and Kubernetes infrastructure across global bare-metal environments. Responsibilities include maintaining high availability, managing control planes and container platforms, troubleshooting system-level incidents, conducting root-cause analysis, building automation and self-service tools, improving observability, and supporting production systems through on-call rotation. The role also collaborates with distributed engineering teams on infrastructure standardization and may support AI/ML workloads.

Engineering Manager, Applied AI leads and coaches engineers while remaining hands-on on client engagements. Responsibilities include reviewing architecture, agent, prompt, and evaluation designs; resolving technical and client challenges; managing staffing and delivery; hiring and onboarding engineers; and improving engineering practices. The role requires strong software engineering experience, Python expertise, client-facing delivery experience, and familiarity with agents, evaluations, multi-agent systems, and AI coding tools.

Designs and operates public, automated benchmarks for data providers. Owns datasets, ground truth, scoring methodology, reproducible evaluation harnesses, weekly releases, public leaderboards, and integration of benchmark results into Alexandria’s provider-selection system. Measures accuracy, coverage, freshness, speed, and cost while communicating findings to engineers, marketers, and vendors.

Develop quantitative models, statistical analyses, experimentation frameworks, and scalable data pipelines to solve product and business challenges. Partner cross-functionally with product, engineering, design, research, and analytics teams to generate actionable insights, improve products, and establish scientific best practices. Apply AI to accelerate workflows while validating AI-assisted outputs and protecting sensitive data.

Plans and leads testing strategies for large enterprise systems across functional, integration, regression, acceptance, performance, stress, load, accessibility, security, and data validation testing. Develops test plans, cases, scripts, automation, and reports; manages defects; integrates tests into CI/CD pipelines; validates databases and system behavior; and collaborates with technical and business teams in Agile environments.

Leads and develops engineering teams while remaining hands-on with applied AI architecture, agents, prompts, evaluations, and production systems. Owns technical decisions, staffing, hiring, client engagement delivery, and converting lessons across projects into repeatable practices and platform capabilities. Requires strong software engineering depth, Python expertise, client-facing delivery experience, and familiarity with agentic and multi-agent systems.

Analyze spatial and product data to improve Lyft’s mapping, routing, and travel-time estimation products. The role designs online experiments, develops performance metrics and analytical frameworks, identifies growth and efficiency opportunities, and translates insights into product and business decisions. The Data Scientist partners with engineers, product managers, and operators while communicating recommendations to senior stakeholders. Responsibilities also include monitoring rider and driver experience and applying statistical analysis, programming, visualization, and machine learning techniques.

Develop advanced statistical models and custom analyses to address client business challenges. Use R, Tableau, SAS, Visual Basic, Excel, and other analytic tools to guide decisions, create deliverables, and implement solutions. Communicate findings through presentations, manage client relationships, provide project updates, and mentor Associates while contributing to consulting engagements.