Top Python Jobs in Toronto

The Data Scientist will manage ML/AI use cases, design models, enhance data products, and mentor team members while collaborating on innovative analytics solutions.

The GTM Data Manager oversees data integration, quality assurance, and analysis to support revenue operations and strategic GTM planning.

As Payments Lead, you will drive technical direction and delivery of software solutions, oversee payments infrastructure, and ensure operational excellence.

You will develop reusable components for DevSecOps, automate security controls, mentor teams, improve internal tooling, and support operational success in a cloud environment.

The Lead DevSecOps will design reusable components, implement automation and security measures, mentor teams, and enhance toolsets for production services.

Drive advancements in CI/CD, ensure build system reliability, develop tooling for remote environments, and promote engineering excellence.

As a DevOps Developer, you'll design and maintain Python-based services on AWS, manage CI/CD pipelines, optimize databases, and collaborate with teams to enhance features, ensuring security and uptime.

As a Fund Accountant, you will manage fund accounting, reporting, and post-trade operations while collaborating with finance and technical teams.

Lead technical initiatives in ML product development focusing on LLM and NLP systems. Mentor engineers, design models, and oversee data strategies while ensuring operational excellence and model performance.

The Data Engineer will build and maintain reliable data pipelines and systems for financial forecasting, ensuring data quality and working with stakeholders to support analysis needs.

The Technical Analyst will support team projects by executing the technical roadmap, collaborating across departments, troubleshooting issues, and assisting with analytics initiatives to enhance marketing performance.

As a Technical Implementation Specialist, you will configure and implement ODAIA's AI-driven platform, collaborating with customers to integrate data assets and build automated ETL workflows.

The Sr./Principal Mixed-Signal Digital Architect will design digital circuits for photonic-based communication, collaborate with teams, and lead product development.

The Deployment Engineer will manage AI inference clusters, optimizing deployment, capacity allocation, and ensuring reliability of pipeline operations across datacenters.

Develop high-performance code for the distributed system, optimizing data structures and algorithms for Cerebras' architecture in AI applications.

The Technical Account Manager ensures the successful deployment and integration of Mattermost for enterprise customers, focusing on cybersecurity and compliance while fostering strong customer relationships.

As a Senior Research Engineer, you will optimize language and vision models on Cerebras hardware, focusing on high-performance ML inference techniques.

Support the design, implementation, and maintenance of data workflows and automation for multi-channel marketing, focusing on reliable data solutions and campaign activation.

Support marketing technology implementations and optimizations. Configure marketing automation, create digital assets, and ensure seamless campaign execution across platforms.

Lead the delivery of scalable kdb+ solutions for financial clients. Design robust architectures, mentor developers, and drive innovation in data management.

Develop and maintain kdb+ applications, analyze time-series data, mentor junior developers, and collaborate with teams to deliver solutions.

Lead the architecture and implementation of payments and billing systems to manage financial transactions, enhance compliance, and mentor engineers.

The Risc-V Architect will analyze AI workloads, design custom RISC-V cores, and lead the architecture efforts at Tenstorrent, improving CPU performance.

As an Agile Test Engineer, you will design and execute testing strategies, leverage AI in testing processes, and collaborate with teams to ensure software quality across various applications.

Lead R&D in ML modeling for chatbots, develop AI-driven systems, design scalable models, and collaborate with cross-functional teams to enhance customer support.