Top Python Jobs in Toronto

The AI/ML Engineer will develop and optimize machine learning models, focusing on conversational systems, multi-agent solutions, and scalability, while collaborating across teams to enhance user experiences.

Design, build, and deploy complex distributed microservices and cloud-based systems. Implement RESTful APIs, third-party integrations using SDKs, and manage package release cycles (CI/CD). Work with AWS/GCP, NoSQL (MongoDB/Elasticsearch) and SQL databases while providing technical leadership and strong cross-team communication.

The Lead Data Scientist will design and implement data-driven solutions, lead a team of data scientists, and collaborate across functions, while managing machine learning pipelines and mentoring junior staff.

You will develop high-performance quantum software components, build benchmarking tools, and lead best practices in software development processes.

Develop high-performance software for optimizing quantum hardware. Responsibilities include authoring libraries, enhancing communication protocols, benchmarking, and ensuring software quality.

Develop and maintain JIT and AOT hybrid compilation pipelines for PennyLane, focusing on algorithm implementation, R&D for hardware platforms, and software quality.

You will develop and expand pennylane.ai, collaborate with teams, maintain high code standards, and architect scalable frontend systems.

As a Manager, Applied Research, you will lead a team of scientists to drive innovative AI research into production solutions, mentor team members, and collaborate with product leaders to define AI strategies.

As a Research Scientist in Neural Reconstruction, you will develop algorithms for 3D/4D scene reconstruction using real-world sensor data, collaborate on large-scale simulation systems, publish research and mentor junior scientists.

As a Software Engineer, you will create tools and pipelines for AI development, manage data solutions for ML teams, and ensure high-quality code.

Develop algorithms for World Models focusing on large-scale modeling for dynamic 4D environments. Conduct research in generative and predictive modeling, collaborate with engineers, and mentor junior scientists.

The Software Engineer will develop Link's investment analytics platform, design application infrastructure, and work directly with business teams on solutions and feedback.

Design and deliver full-stack features across notebook services, container runtimes, and UI (Go/Python backend, TypeScript/React frontend). Own medium-to-large projects end-to-end, improve runtime management, reproducibility, security/compliance, and observability, ensure reliability in regulated or air-gapped environments, participate in on-call rotation, and mentor junior engineers.

Define, implement, execute and maintain test plans and cases for ADAS controllers. Automate tests, develop and troubleshoot HIL bench tests, use Python and CAN/Ethernet tools (INCA, CANoe, CANalyzer, VSpy), produce reports, and apply calibration/validation and AI tools to improve test coverage and productivity.

As a Data Analyst at Lyft, you will collaborate with teams to analyze data, streamline processes, and provide actionable insights to improve performance in bikeshare and scooter markets.

The Senior Software Engineer will design and develop AI-powered tools to automate quality assurance processes, improve developer workflows, and enhance testing efficiency, directly impacting developer productivity and satisfaction.

As a Staff Backend Engineer, you'll design and evolve backend services, architect data models, mentor engineers, and influence architecture and product direction to enhance enterprise-grade performance.

As a Staff Backend Engineer, you will develop complex backend solutions, focusing on the Spark-based data platform while ensuring code quality and collaborating closely with teams.

As a Senior Solutions Engineer, you will lead technical engagements, design scalable data solutions, and mentor junior team members while collaborating cross-functionally.

Develops and executes software validation and test plans for rail signalling systems. Creates test automation, analyzes failures, conducts lab and simulation stress tests, and reports results. Collaborates with engineering teams, follows Agile/DevOps processes, and supports safety-driven testing and continuous improvement.

Eight-month paid software analyst internship contributing to R&T projects for urban rail signaling: develop and test software, analyze lab/field results, work with sensors and real-time systems, implement ML/LLM and agentic workflow solutions, and support prototype and proof-of-concept development in a hybrid team environment.

Work with senior engineers on safety-critical railway software: analyse, design, develop, and test embedded software and automation tooling. Contribute code in C and Python, develop scripts and CI/CD toolchain improvements, document solutions, troubleshoot automation issues, and collaborate across cross-functional teams in a hybrid paid internship.

Build and maintain backend and full-stack marketplace features while supporting ML Ops infrastructure (model deployment, feature stores, real-time pipelines, monitoring). Collaborate with data scientists to bring models to production, write well-tested code, address performance and scalability issues, and contribute to technical planning and cross-functional communication.

Build and maintain full-stack marketplace features and support ML Ops infrastructure (model deployment, feature stores, real-time pipelines, monitoring) on Chalk and Vertex AI. Collaborate with data scientists to productionize models, write well-tested code, address performance/scalability issues, and contribute to technical planning.

Build and own end-to-end backend systems for forecasting and agentic LLM research: design, deploy, monitor, debug, and harden features and pipelines (benchmarks, agents, production services). Prototype quickly, work with LLM APIs and coding agents, and collaborate with researchers to improve evaluation and forecasting tools.