Top Python Jobs in Toronto

As a DevOps Engineer, you'll automate backend infrastructure, streamline deployments, manage cloud services, and enforce security best practices for scalable and reliable systems.

The DevOps Engineer - Mobile will design and maintain CI/CD pipelines for iOS and Android apps, automate workflows, manage cloud infrastructure, and enforce security best practices.

The DevOps Engineer will design, automate, and maintain backend infrastructure, streamline deployments, manage cloud environments, and monitor systems to ensure reliability and cost-effectiveness.

Lead a team of Python developers and statistical analysts to build, deploy and integrate Hyperexponential pricing solutions for commercial lines. Partner with actuaries, underwriters and IT to gather requirements, prioritize work, mentor engineers, apply software engineering best practices (TDD, modular code, Git), and drive delivery into production.

Design, build, and own CI/build/test pipelines for a compiler/runtime/simulator stack; scale and parallelize large test suites, manage heterogeneous CI runner fleets and scarce hardware, implement perf-regression baselines and observability, and define hermetic, safe-by-default build and test standards to maximize developer velocity.

Lead and execute independent experimental projects on 3D genome organization in cancer using Hi-C/HiChIP and complementary epigenomic assays (ATAC-seq, CUT&RUN/CUT&Tag). Prepare NGS libraries, work with organoid models, integrate bulk, single-cell, and spatial multi-omics, collaborate with computational scientists, mentor trainees, and contribute to manuscripts and grant development.

The Robotics Engineer will design and tune control systems, integrate hardware and software, and work with a team to enhance robot behaviors, emphasizing hands-on experience with robotics and embedded systems.

As an intern, you'll develop software and machine learning systems for robots, focusing on perception, intelligence, behavior, and real-time software integration.

The ML Engineer will develop and advance multimodal models for robot perception and behavior, integrating these systems into hardware while collaborating closely with robotics engineers.

The Data Scientist 2 will engage in the full data science lifecycle, including data extraction, model development, and deployment to meet business needs.

Lead and manage forward-deployed engineering teams to design, build, and deliver scalable, secure LLM/AI solutions for customers. Provide technical architecture guidance, drive MLOps/LLMOps best practices, oversee delivery of POCs and production systems, hire and develop engineers, and collaborate with Product, Sales, and Customer Success to shape product roadmaps and reusable AI frameworks.

The Clinical Data Scientist designs and executes data assessment frameworks, evaluates RWD fitness, and supports evidence generation across Sanofi's enterprise, ensuring optimal data usage and collaboration across teams.

As a Staff Full Stack Software Engineer, you will design and build foundational infrastructure, develop enterprise features, and ensure system reliability handling sensitive legal data.

As an Engineering Manager at Harvey, you will lead a full-stack team, oversee core product delivery, and ensure high-quality user experiences by combining technical design and product vision.

Lead end-to-end ML and data strategy across complex enterprise systems. Design and implement advanced statistical and machine learning solutions (including NLP and computer vision), architect data governance and lakehouse/warehouse integrations, drive AI evaluation and governance, and rapidly prototype solutions. Influence multiple teams, translate business needs into technical solutions, and discover ambiguous problems through user immersion to deliver measurable business impact.

As a Data Scientist II, you will build and deliver data science solutions, validate models, support teams, and communicate insights to stakeholders.

As a Lead Test Engineer, you will design test strategies, implement automation, evaluate user experience, and ensure overall feature quality while collaborating with cross-functional teams.

The Solutions Engineer will provide technical expertise for customer implementations and collaborate with various teams to improve the product, focusing on integration through APIs and Infrastructure as Code.

Develop and enhance core banking applications through requirements analysis, coding, testing, debugging, documentation, deployment, and production support. Partner with business and technical stakeholders to deliver scalable solutions, improve processes, automate workflows, and enhance user experience. Participate in code reviews, technology roadmap discussions, continuous improvement initiatives, and an on-call rotation for troubleshooting critical production systems.

Design and implement wafer- and package-level ATE test solutions for silicon photonics products. Develop characterization and manufacturing test plans, debug failures with cross-functional teams, partner with OSATs and foundries, optimize yield and test time for HVM, and write/maintain test scripts and tools to support production and customer deployment.

Lead DevEx strategy and build developer platforms, CI/CD pipelines, and automation to improve productivity, quality, and reliability. Partner with engineering leaders, define golden paths, reduce tooling fragmentation, and iterate on AI-assisted tooling and LLM evaluation frameworks to support hundreds of engineers.

As a Senior or Staff Software Engineer on the Localization team, you will design algorithms for state estimation systems, optimizing multi-sensor data fusion for real-time vehicle localization in autonomous driving.

As a Senior Software Engineer on the Mapping team, you will architect and develop robust, scalable systems for autonomous vehicle mapping, collaborating with multidisciplinary experts and handling complex data processing.

The role involves designing and validating data and AI architectures, collaborating with customers, and ensuring scalable, secure solutions are implemented in enterprise environments.

Lead design, development, testing, implementation and support of data and AI products. Translate business requirements, provide technical direction, mentor developers, build automation and frameworks, improve delivery processes, and perform data analysis, profiling and regression testing.