Top Python Jobs in Toronto

The AI Engineer will design and develop scalable AI solutions for finance, ensuring compliance and collaboration across teams. Responsibilities include coding, model lifecycle management, automation, and technical mentoring.

As a full-stack software engineer intern, you'll collaborate with senior engineers to write quality code, build AI-driven products, and improve engineering productivity.

As an AI Product Engineer at Puzzle Cats, you will develop and enhance AI-driven mobile game experiences, collaborating across teams to rapidly prototype, ship, and iterate on features that can quickly reach millions of players.

The Senior DevOps Engineer will work on product development, ensuring smooth operations of systems, and improving CI/CD workflows while addressing security vulnerabilities and system health monitoring.

The Vulnerability Management Lead oversees the vulnerability management program, ensuring effective identification, assessment, and remediation of vulnerabilities across varied environments.

The role involves designing and tuning control systems for robotics, integrating hardware, developing control algorithms, and collaborating with engineers to enhance robot motion and responsiveness.

As a Data Developer, you'll build and optimize data pipelines, collaborate with cross-functional teams, support data architecture, and ensure data quality along with mentoring on best practices.

The QA Analyst is responsible for designing QA processes, collaborating with teams on testing standards, performing functional and integration testing, and coaching best practices to ensure software quality in a fast-paced SaaS environment.

The Sales Engineer will manage technical relationships, design AI/ML solutions, deliver demos, train customers, and provide feedback to product teams.

The DevSecOps Engineer will lead security initiatives by implementing security controls, automating workflows, mentoring juniors, and collaborating with teams on security best practices.

The Performance Engineer - Inference will optimize model inference speed and throughput, debug low-level kernel performance, and develop tools to visualize performance data.

Lead post-silicon bring-up and optimization of wafer-scale engines: develop debug flows, HW-SW codesign optimizations, build large-scale test infrastructure, create self-checking metrics and instrumentation, and collaborate across silicon, performance, and software teams to improve production performance and release processes.

Design and implement system-level debugging, validation, and observability platforms. Build automated anomaly detection, visualization and analysis tools, and frameworks for failure classification and regression detection. Extend compilers, runtimes, and instrumentation for advanced profiling. Improve bring-up and low-level debug workflows, partner cross-functionally across hardware, firmware, compiler and runtime teams, lead high-impact initiatives, and support incident response and long-term corrective actions.

Lead post-silicon bring-up and performance optimizations for Cerebras Wafer Scale Engines. Develop/debug production-ready flows, instrumentation, and self-checking metrics. Build infrastructure for large-scale silicon workload testing, collaborate with silicon architects, performance and software teams, and streamline CI/CD and release workflows.

The role involves leading engineering teams in product development, driving innovation in software architecture, and integrating AI tools while providing mentorship and technical authority.

Lead Java AI Developer responsible for application systems analysis and programming, enhancing risk management systems, and guiding mid-level developers. Requires in-depth Java and AI tool expertise.

The Tech Lead/Solution Architect will design and deliver cloud solutions, lead architecture reviews, coordinate teams, and engage with clients to execute data and application projects.

The Product Analyst will oversee product analytics, collaborate with teams, define metrics, build dashboards, and improve data quality in a hybrid work environment.

The Lead Research Engineer will provide technical leadership, develop scalable ML solutions, and collaborate with teams to innovate and deliver products that enhance customer experiences in legal, accounting, and government sectors.

As Engineering Manager, you will manage a technical team, drive technical strategy, mentor developers, and ensure effective product delivery while aligning with organizational goals.

The Senior Data Scientist will enhance Relay's data capabilities, building predictive models and supporting data-driven decisions across teams while mentoring junior data scientists.

Own cloud operational health, architecture intelligence, and cost optimization. Analyze cloud spend, build dashboards/reporting, enforce governance, review architecture for cost impact, and translate technical findings for engineering, finance, and executives.

Build and scale AI data and ML infrastructure: evaluation systems, fine-tuning pipelines, agent-first product surfaces, high-throughput data workflows, and integrations of new models into production.

Architect and build scalable, secure backend microservices for Payments, Disbursements, or GRC squads. Implement payment and disbursement workflows, KYC/compliance pipelines, and cloud infrastructure using Google Cloud and Kubernetes. Collaborate cross-functionally, mentor junior engineers, and optimize systems for high throughput, reliability, and regulatory compliance.

Design, build, and scale backend microservices for Payments, Disbursements, or GRC squads. Implement secure, high-performance payment and disbursement workflows, KYC/compliance systems, and cloud infrastructure on Google Cloud. Collaborate cross-functionally, mentor junior engineers, and iterate on platform architecture to handle millions of daily requests.