Top Python Jobs in Toronto

The Principal Platform Engineer will design and build scalable ML platforms, develop cloud-native infrastructure, and manage the model lifecycle in enterprise environments, focusing on MLOps capabilities and mentoring engineers.

The Senior Platform Engineer will build AI systems, develop APIs, support scalability, and integrate AI capabilities for financial services clients.

RAVL is seeking Senior ML Platform Engineers to build and scale machine learning platforms, develop ML pipelines, and support MLOps workflows in cloud environments.

Perform deep root-cause debugging across frontend-to-backend stacks, troubleshoot and read SDK source, support enterprise customers on architecture, and build agentic automation (LLM orchestration, MCP, internal APIs) to create deterministic autonomous support paths.

Design and develop high-performance distributed software for scalable AI training systems, focusing on data pipelines and system efficiency.

Develop and automate configuration for distributed clusters, create monitoring tools, manage cloud operations, and ensure system reliability for Cerebras AI supercomputers.

Embed with cross-functional teams to map high-value workflows, design agentic or deterministic automated solutions, build production-ready tools, and run them with monitoring, evals, and continuous improvement. Balance stakeholder discovery, systems integration, full-stack development, and operational ownership to increase throughput and reduce cost.

Develop and deploy scalable deep learning and reinforcement learning systems, optimize performance, and collaborate with data teams at Quincus.

As a Senior Deployment Engineer, you'll manage the deployment lifecycle of Atolio's enterprise search platform in diverse environments, ensuring scalability and security while collaborating with internal and client teams.

Lead technical SEO for content marketing: conduct technical audits, improve search and AI visibility (GEO/AEO), run SEO reporting and recommendations, and build AI-assisted workflows for content production and analysis.

As a Backend Engineer, you will architect, build, and deploy systems for our data science platform, collaborating with a cross-functional team to enhance machine learning practices.

Seeking Data Platform Engineers to design, build, and manage scalable data pipelines and analytic query engines while ensuring data integrity and performance optimization.

As a Backend Software Engineer, you'll develop critical backend systems focusing on APIs, data processing, and infrastructure while ensuring high-quality service delivery and robust architecture.

Lead development of backend systems and integrations to ingest and process large-scale data, design secure multi-tenant SaaS architectures, own APIs and platform work, mentor engineers, author technical proposals, and troubleshoot production issues to minimize downtime.

Lead structuring and execution of structured financings (RMBS, ABS, master trust, asset sales), develop a secondary trading platform, manage interest-rate and credit risk, build cash-flow models and analytics (Intex/Excel), execute go-to-market financing strategies, and provide investor, rating agency, and capital provider support.

Lead end-to-end AI solutions as a forward-deployed engineer: scope, design, and deploy ML/LLM systems; partner with clients and stakeholders; build infrastructure, data pipelines, and reusable platform components; mentor engineers; own projects from discovery through production and provide on-call support.

Build and own end-to-end fullstack features for a marketing analytics dashboard. Lead technical direction, collaborate with product and customer teams, optimize frontend performance, create and maintain APIs, ensure reliability and scalability, and mentor other engineers.

As a Senior Full Stack Software Engineer at Doxel, you will design and develop applications for project management, focusing on complex data handling and intuitive UI. Your role involves collaborating across teams and providing technical leadership in software projects.

Design, build, and operate backend systems and infrastructure. Work on system design, databases (SQL/NoSQL), cloud platforms, containerization, IaC, CI/CD, monitoring/logging, networking, security, and Linux fundamentals in a fast-paced startup environment.

Lead development of cloud data platforms and end-to-end data pipelines using AWS/Snowflake and big-data technologies (Spark, Hive, Iceberg). Automate builds and deployments with Bash/Python shell scripting, apply CI/CD and Medallion Architecture, perform data modeling and warehousing, and collaborate across teams. Pharma/AbbVie experience preferred.

Design, build, and deploy AI agents and automations to streamline pre-sales processes (discovery, demos, RFPs, POCs). Integrate AI tools with CRM and knowledge systems, prototype quickly, train and support solutions engineers, monitor automation performance, and document scalable workflows to improve adoption and impact.

Build and scale a live ML data streaming analytics platform, lead greenfield real-time processing projects (Python/Rust), and design reliable backend services using cloud and orchestration tools.

Lead quality strategy and testing for LLM-powered and agentic systems. Design evaluation frameworks, build scalable automated test suites, define quality metrics, integrate tests into CI/CD, mentor QE org, and partner with cross-functional teams to ensure release readiness for AI products.

Lead and resolve high-severity post-sales technical escalations through deep-dive investigation, reproduction, and engineering handoff. Own customer calls, collect logs/evidence, file bug reports, monitor patterns, and improve tooling and runbooks in partnership with Support and Engineering.

Founding technical role to design, build, and deploy internal AI tools and agents using LLMs and retrieval systems. Partner with investors and the data team to accelerate sourcing, diligence, portfolio insights, and define CRV's AI strategy through rapid prototyping and production-grade systems.