Top Python Jobs in Toronto

Design, develop, fine-tune, and optimize generative deep learning models (GANs, VAEs, transformers). Collaborate with cross-functional teams to integrate and deploy AI solutions, troubleshoot model issues, document models, and communicate technical concepts to non-technical stakeholders.

Design and architect large-scale distributed Big Data solutions using Java, Spark, and Hadoop/Cloudera. Lead global teams to build high-volume data processing and analytics pipelines, ensure robust testing (JUnit), and apply scripting for automation and data analysis.

Build and maintain responsive Angular UI components, collaborate with UX and backend teams, implement REST APIs and Python backend scripts, integrate basic ML models into data workflows, and participate in the full SDLC within Agile teams while ensuring code quality and performance.

Senior Java Big Data Developer with 8+ years building applications on Cloudera/Hadoop ecosystems using Spark and MapReduce. Responsible for designing performant Java (1.8+) solutions, data analysis of large datasets, unit testing (JUnit), and collaborating with/managing global technology teams. Preferred skills include Unix/Python scripting and familiarity with Hive, Impala, YARN, and Kafka.

Lead design and implementation of GenAI platform components and secure APIs. Drive end-to-end AI development from research to production, apply DevOps for scalable deployments, collaborate with cross-functional teams, and stay current with GenAI advances to deliver customer value.

Build and scale the internal developer platform: create tools, services and automation (CI/CD, canaries, feature flags, access workflows) using IaC (Pulumi/Python) and Kubernetes to enable safe, fast shipping. Drive platform initiatives, mentor teams, lead AI tool adoption for engineering, participate in on-call and design/code reviews, and ship major improvements across the organization.

Design, build, ship, and support backend services and end-to-end features focused on reliability, scalability, and performance. Debug production issues, write and debug SQL, follow testing best practices, collaborate in a remote team, participate in on-call, and contribute to architecture and roadmap decisions.

Proactively explore RevenueCat data to identify customer problems and opportunities. Translate ambiguous product questions into analyses and production-grade predictive/descriptive models. Partner with Product, Engineering, and Analytics to shape roadmaps, define experimentation and benchmarking approaches, deploy and iterate on models powering customer-facing features, and communicate insights across technical and non-technical audiences.

Design, build, ship, and maintain end-to-end product features across frontend, backend, and data layers. Own projects from definition through production, improve reliability and scalability, collaborate with product and design, mentor engineers, and engage with customers to solve real user problems.

Founding Data Scientist for RC Capital responsible for building underwriting, fraud detection, anomaly detection, and lead-qualification models; integrating risk signals into product flows; deploying and monitoring production models; analyzing cross-platform revenue data; and defining DS strategy to scale fintech products.

Conduct market and competitive intelligence research for quantum computing products; track competitors, patents, publications, financial signals, and industry trends. Use AI-enabled tools and dashboards (Tableau/Power BI/Python) to gather, analyze, and visualize data. Produce reports and presentations to inform product strategy and support cross-functional teams.

The GTM Engineer will enhance and manage enrichment infrastructure, scoring pipelines, and event tooling while writing production code and ensuring data accuracy within GTM operations.

Lead and grow a Detection engineering team building tools, applications, and infrastructure for fraud and abuse detection. Collaborate with engineers, scientists, and stakeholders to design, implement, and review scalable systems and features, mentor engineers, and contribute to code and architecture to improve detection capabilities.

Design and implement backend services, APIs, CI/CD and cloud infrastructure using IaC and Kubernetes. Build internal developer tooling, define observability and security standards, lead incident response, and mentor engineers while applying AI tools to improve productivity and delivery.

The Sr. Software Engineer II will design, develop and maintain distributed systems, ensuring scalability, reliability, and performance while leading and mentoring team members.

Lead and grow a services engineering team owning backend systems, APIs, integrations, and operational reliability. Partner with product and operations to define customer-focused outcomes, drive technical direction across Python/Go/Ruby services, improve execution standards, remove blockers, and develop engineers. Measure success by customer value, system health, and team performance.

Lead QA strategy and execution for web, API, and mobile. Establish Playwright automation, integrate AI-assisted testing into CI/CD, mentor QA engineers, improve regression stability and coverage, define release validation standards, and track quality KPIs.

Design and advance core infrastructure for engineering, ensure Kubernetes reliability, automate operations, and support AI infrastructure.

Operate and maintain Kepler's satellite constellation, perform LEOP and commissioning, resolve anomalies, analyze performance, develop/improve procedures and automation tools, support launches, and participate in on-call shift rotations to ensure continuous service.

Lead machine-level systems engineering for robotics: derive requirements from deployment targets, define use cases and interfaces, build error/performance budgets, run verification/validation, own safety architecture, support integration, field-commission devices, and drive cross-functional alignment.

Build and own hardware test function for robotic systems: design fixtures and rigs, create test plans, instrument DAQ systems, run environmental and durability tests, diagnose root causes, build reliability models, and automate test reporting to qualify machines for field deployment.

Lead design and implementation of backend services and distributed systems for real-time AI automation. Build scalable, observable microservices, streaming data pipelines, and async event-driven architectures. Collaborate across frontend, product, and DevOps to ensure performance, reliability, and seamless integration at scale.

Design, build, and deploy AI-enhanced SIEM/SOAR detections, automations, and analytics. Integrate telemetry and security tools, develop AI/ML threat models and UEBA, optimize pipelines, and support SOC operations with automated playbooks and enriched alerting.

Own and set technical direction for the Everand backend, building scalable, reliable systems for discoverability, personalization, and core consumption journeys. Drive architecture, platform health (CI/CD, staging, DBs, queues, cost, observability), mentor engineers, lead cross-team planning, modernize legacy systems, and partner with product, design, analytics, web/mobile, and ML to support experimentation and telemetry-driven decisions.

As a Guidewire Rating Developer, you'll design and maintain rating logic within Guidewire PolicyCenter, collaborate with teams on integration and improvements, and participate in code reviews and QA support.