Top Python Jobs in Toronto

Responsible for designing and implementing scalable backend services for games, driving technical innovation, and mentoring engineers within a collaborative team.

The Network Specialist will support and enhance the company's global network by designing, implementing, and optimizing network infrastructure and application delivery solutions across various environments.

Seeking a Full-stack Software Developer Specialist to design and deliver scalable applications, focusing on data engineering with Python and Databricks. Key responsibilities include developing data pipelines, implementing APIs, testing, and collaborating within a team structure.

As an AI Developer II, you will deliver AI and machine learning solutions, work on complex projects, and evolve software products, while collaborating with multidisciplinary teams.

Lead and manage a team of engineers to design, develop and maintain the North AI workspace platform, enabling seamless integration of enterprise AI solutions.

As a Forward Deployed Engineer, you will build and ship features for an AI workspace platform, develop autonomous agents, and manage end-to-end deployments, collaborating closely with clients in various sectors.

The role involves designing and implementing a data and ML platform, optimizing data ingestion, and driving ML workflows, ensuring scalability and reliability.

The Staff Verification Engineer will drive pre-silicon verification of SoCs, build testbenches, analyze bugs, and collaborate with various teams on IP verification methodologies.

The Technical Lead will design and implement backend systems, mentor engineers, optimize performance, and manage cloud architecture while ensuring scalable and reliable data processing.

Contribute expertise in optics and photonics for SNSPD development, operate cryogenic systems, and enhance performance and scalability of SNSPD technology.

As a Developer Experience Engineer, you will improve developer productivity by building tools and systems, advocating best practices, and addressing pain points within engineering teams.

The Deployment Engineer will build and operate AI inference clusters, ensure scalable deployments, optimize allocation, and maintain infrastructure. Responsibilities include software updates, telemetry development, and collaborative improvements with teams.

Design and implement a highly available, distributed, and secure cloud-based system. Collaborate with teams to optimize infrastructure and ensure robust application delivery.

The Architect will design and implement a highly available, distributed, and secure cloud-based system, optimizing existing infrastructure and collaborating with various teams.

The role involves leading data engineering projects, building scalable data models, optimizing workflows, and ensuring data quality while collaborating with cross-functional teams.

The Quality Engineering Senior Programmer Analyst will maintain automation frameworks, perform tests, recommend improvements, and ensure software quality. Close collaboration with stakeholders is essential.

Lead the software verification team to ensure high-quality, reliable software releases by defining verification strategies and managing the team.

Lead and manage a software verification team, define verification strategies, ensure compliance with standards, and drive test automation efforts.

The role involves leading projects, ensuring quality code, collaborating with teams, and innovating mapping solutions for Lyft's passenger and driver experiences.

Lead and mentor a data science team to enhance the Rider App experience through machine learning, analytics, and experimentation. Partner with stakeholders to drive data-driven decisions and innovation.

The Principal QA Developer leads the quality strategy, builds test automation frameworks, and partners with engineering to enhance reporting reliability and system integrity.

The Principal Software Developer will architect and evolve backend systems using Node.js and Python, design RESTful APIs, lead teams, and maintain high reliability and performance in a scalable environment.

Develop and optimize auto-labelling systems using ML and computer vision, manage data pipelines, and collaborate with researchers.

Intern will be part of a team developing AI algorithms for Autonomous Vehicles, contributing to research projects and publications.

Lead cross-functional teams to integrate high-performance IP into FPGA products, manage team engineers, and develop memory interconnect architecture.