Top Python Jobs in Toronto

Build and lead Clio’s threat intelligence program, including intelligence requirements, platform implementation, adversary and campaign tracking, original infrastructure and malware research, fraud and abuse analysis, and executive briefings. Translate intelligence into detection requirements, red-team priorities, and payment fraud controls. Manage intelligence vendors, participate in industry information sharing, collaborate with blue teams, automate collection and analysis, and mentor junior analysts.

Build and ship full-stack AI product features using Python, Node.js, React, and TypeScript. Design APIs, integrations, data pipelines, and scalable architectures while supporting cloud infrastructure, CI/CD, security, observability, and reliability. Own projects from technical design through deployment and iteration, collaborate cross-functionally, lead code reviews, mentor developers, and improve engineering practices.

As a Senior Software Engineer, Full Stack, you will build backend services and APIs for a document analysis platform, focusing on server-side architecture and data processing, while also contributing to frontend features as needed.

Develop, test, deploy, and support enterprise-grade applications, services, integrations, and data-enabled solutions using Microsoft technologies and Azure. Participate in the full SDLC, CI/CD, DevSecOps, troubleshooting, documentation, and cross-functional collaboration. Apply AI-assisted development tools and integrate responsible AI capabilities into secure, maintainable business solutions.

Leads manager research and oversight for NEI Investments and the Managed Asset Program, including manager selection, due diligence, sub-advisor oversight, performance evaluation, and investment recommendations across public, private, and alternative markets. Directs a research team, develops analytical capabilities, oversees external manager relationships, improves research frameworks, and provides investment insights to senior leaders, clients, and sales teams.

Own production online camera calibration, SLAM/VIO systems, and fleet-wide calibration drift monitoring for robotics devices. Develop video-based calibration refinement, maintain calibration databases and version history, coordinate with hardware teams on sensor parameters and synchronization, and build visualization tools for operations and research. The role requires extensive experience with SLAM, VIO, SfM, multi-sensor calibration, optimization, and scalable C++ and Python engineering. It is on-site with periodic travel to a hardware site.

Develop and own classical computer vision systems for 3D hand reconstruction, including multi-view geometry, camera calibration, temporal filtering, inverse kinematics, and physical constraints. Convert model predictions into clean, validated spatial data and maintain scalable delivery pipelines. Build QA metrics, visualizers, dashboards, and failure-analysis tools while partnering with research teams on robotics and embodied AI applications.

Develop generative and physics-based models to infer full-body human motion from egocentric and partial observations. Train motion priors, enforce physical consistency, estimate contacts and ground planes, and deliver MHR/SOMA-X outputs for production robotics pipelines. Define evaluation metrics, commission motion-capture and sensor data, implement research code, and publish results.

Own global IT operations across Toronto, Pune, and Krakow, including onboarding, offboarding, office infrastructure, SaaS administration, procurement, vendor management, budgeting, capital planning, endpoint security, identity administration, and IT service metrics. Lead an IT team, partner with Security, SRE, Finance, and People teams, improve processes through documentation and automation, and report operational performance and spending to executives.

Design, build, and operate AWS cloud platforms supporting production generative, agentic, and conversational AI workloads. Develop reusable AWS CDK infrastructure in TypeScript or Python, containerized ECS workloads, CI/CD and GitOps workflows, AI gateways, observability, security, governance, reliability, and cost optimization capabilities. Partner with AI, data, software, and security teams to transition prototypes into resilient production services within a regulated pharmaceutical environment.

Partner with business leaders to scale operations and deliver high-impact cross-functional projects. Improve core processes, evolve user journeys, build actionable data reporting, prioritize growth roadmaps, implement and optimize enterprise software, and lead change management while coordinating stakeholders across the company.

Research and develop neural 3D reconstruction models that recover geometry, pose, deformability, and physical properties of manipulated objects from monocular egocentric video. Build generative refinement, contact-aware reconstruction, and simulatable-object prototypes using deep learning, 3D geometry, and differentiable rendering. Define research direction, evaluate challenging real-world data, prototype in Python and PyTorch, and hand successful methods to an integrations researcher for productionization.

Build and deliver production backend, platform, and AI capabilities using C#/.NET and Python. Develop distributed systems, LLM applications, AI agents, retrieval workflows, MCP servers, document understanding, and scalable AI infrastructure. Provide hands-on Staff-level technical leadership through architecture, coding, technical direction, mentoring, deployment, reliability, safety controls, and production operations.

Develop and validate machine learning and statistical models for consumer credit risk, fraud, portfolio management, IFRS 9 forecasting, and borrower behavior. Build explainable predictive models, automate analytical processes, identify quality data sources, document methodologies, and translate complex findings into actionable business insights. The role partners with cross-functional teams and balances model performance, interpretability, scalability, and commercial impact.

Own the technical direction, development, reliability, and migration of Faire’s data infrastructure. Build CDC and streaming ingestion pipelines from production databases through Kafka into Iceberg on S3, operate Airflow and Fivetran, and implement data contracts, quality checks, SLAs, and observability. Lead cross-team initiatives, mentor engineers, manage incidents and on-call responsibilities, and partner with data scientists, analysts, and engineering teams to deliver dependable analytical data platforms.

Software engineering interns will complete scoped technical projects, build and test production-oriented code, contribute to Pinterest products and infrastructure, and collaborate with engineering, product, design, data, and mentors. Interns will develop professional skills, use AI responsibly in software development, participate in learning opportunities, and contribute ideas while gaining experience with large-scale systems.

Machine Learning Interns will own scoped ML projects from problem definition through experimentation, implementation, testing, and communication. They will develop and evaluate models for discovery, advertising, and search using techniques such as NLP and graph-based modeling; analyze data; contribute to applied AI research; write maintainable code; and collaborate with engineering, product, and data teams.

Drive DevOps and SRE initiatives across cloud-native data infrastructure. Deploy and manage Kubernetes workloads on AWS and GCP, provision infrastructure with Terraform, maintain CI/CD pipelines, develop Python automation, improve observability and reliability, optimize cloud costs, enforce security standards, and influence cross-functional data and engineering teams.

Design and build SWTCH’s automated end-to-end testing practice from the ground up. Develop functional, regression, integration, and E2E test suites for web, mobile, API, and backend products; integrate testing into CI/CD; investigate failures; track defects; and improve coverage. Partner with Product and Engineering to define testable requirements and edge cases, perform exploratory testing, and mentor engineers in automation practices.

Lead the development of reusable DevSecOps and cloud components, delivering automation, security controls, zero-touch deployments, telemetry, dashboards, and high-availability platform support. Partner with product and engineering teams to improve operational ownership, maintain secure configurations and baselines, modernize tooling, and support reliable production services. Mentor teams, deliver group OKRs, and communicate complex technical concepts clearly.

Leads infrastructure and platform demand planning across compute, cloud, containers, networking, databases, storage, security, observability and service operations. Coordinates dependencies, estimates, risks, governance, operational readiness, financial analysis and delivery commitments across engineering teams and service providers. Translates technical complexity into business recommendations while supporting secure, automated platform consumption and responsible AI adoption.

Conduct statistical analysis, machine learning, predictive modeling, causal inference, experimentation, and time-series forecasting. Build scalable data pipelines, dashboards, reports, and production models using Python or R, SQL, and Spark. Analyze complex datasets, identify patterns and anomalies, optimize model performance, generate actionable recommendations, and present findings to data science and partner teams. The intern will collaborate with multidisciplinary stakeholders and work on fraud, losses, and financial crime problems.

As a Software Engineer - AI, you will design, develop, and deploy AI solutions for legal applications, working with clients and technical teams to enhance legal workflows and improve AI outputs.

Leads functional, end-to-end, UAT, and automated testing for complex multi-tier applications. Builds and maintains automation frameworks using Java and TypeScript, monitors product and process quality, documents findings, analyzes root causes, tracks corrective actions, verifies traceability, and reports quality metrics. Collaborates with project managers, users, and global teams to support software releases, ensure SDLC standards, and identify improvements. Provides informal guidance to newer team members and supports compliance and risk controls.

Conduct applied research in machine learning and generative AI for eBay’s selling organization. Develop causal pricing models, LLM-based selling agents, evaluation frameworks, lightweight distilled models, and marketplace feedback analyses. Translate research into reliable production systems, partnering with Product, Engineering, and Data teams. Own measurable business outcomes, contribute to research strategy, and mentor junior researchers.