Top Python Jobs in Toronto

Lead design, development, deployment, and operational support of scalable cloud data platforms and ELT/ETL pipelines on Azure. Build data products for analytics and AI, optimize performance/cost, implement CI/CD and observability, collaborate with stakeholders, and troubleshoot complex data workflows using Snowflake, dbt, Python/PySpark, and orchestration tools.

Site Reliability Engineers apply software and systems engineering to improve reliability, performance, and operability. They deploy, configure, monitor, recover, and scale services, participate in on-call rotations, evaluate products before and after releases, and spend at least half their time engineering away problems while collaborating with teammates.

Lead analytics for Safety & Customer Care by partnering cross-functionally to define metrics, build dashboards, design and analyze A/B tests, monitor KPIs, and deliver data-driven recommendations to improve customer support experience and inform senior leadership.

Analyze complex structured and unstructured datasets, develop predictive models, apply statistical and machine learning methods, identify data quality issues, and generate actionable insights. The role integrates data from multiple sources, supports modernization and governance initiatives, creates dashboards and analytical frameworks, and communicates findings to technical and non-technical stakeholders. It is hybrid in Toronto with onsite work required five days as project needs dictate.

Own AWS and Kubernetes reliability, deployments, observability, incident response, infrastructure as code, CI/CD, and compliance controls for SOC 2 and PCI-DSS. Build scalable platform foundations, AI infrastructure, and greenfield product infrastructure while improving cost efficiency, security, vendor flexibility, and deployment consistency. Participate in on-call support and partner with security and engineering teams across backend, mobile, data, ML, and AI.

Leads technical and writing teams delivering generative AI products, coordinating customers, data, product, and research teams. Tracks annotator metrics, manages labeling initiatives, creates prompts and responses, develops stakeholder guidelines, and trains teams on LLM and dataset best practices. The role includes customer interaction, quality assurance, and exposure to potentially toxic or sensitive content.

eBay is hiring ML Scientists and ML Engineers to design advanced models for ranking, recommendations, personalization, and pricing, and to productionize those models. Responsibilities include feature engineering with Zipline, building ETL/ELT and inference pipelines, MLOps, model serving, monitoring, deployment automation, and cost/performance optimization.

Design, build, and operate scalable real-time and batch data pipelines using Kafka, Spark, Flink, Airflow, Databricks, AWS, and dbt. Implement data quality frameworks, optimize distributed workloads, and develop reliable cloud-native data platforms. Own initiatives from architecture through production support while collaborating with Data Science, Product, Analytics, and Engineering teams. Create reusable engineering patterns, improve system scalability and performance, and maintain documentation for critical data systems.

Design, develop, and own scalable real-time and batch data pipelines using Kafka, Spark, Flink, Airflow, Databricks, and AWS. Implement data quality frameworks, oversee projects from design through long-term support, identify scalability risks, document systems, and collaborate with data science, product, and engineering teams to guide technical roadmaps.

Build and ship features for Cohere’s North AI workspace platform, develop autonomous agents that interact with sensitive enterprise data, and deploy highly performant, secure applications in low-resource environments. Collaborate with researchers to productionize advanced AI models and techniques while contributing across the full stack using Python and React.

Conduct fundamental research in video generation, video editing, and 3D computer vision. Develop state-of-the-art AI and computer vision algorithms, create research prototypes, solve real-world problems, publish in leading conferences, integrate innovations into Huawei products, and supervise interns within collaborative R&D projects.

Conduct research and development in computer vision, deep learning, LLMs, and VLMs. Develop image and video understanding or synthesis systems, multimodal reasoning and agentic applications, and optimize models for mobile computing constraints. Responsibilities include prompt engineering, model adaptation, fine-tuning, evaluation, and reinforcement-learning-based post-training. The role also involves academic research and applying machine learning techniques to real-world problems.

Conduct research and develop state-of-the-art speech and audio AI technologies. Responsibilities include literature reviews, algorithm implementation, data collection and analysis, deep learning and signal processing, and documenting, presenting, and publishing results while collaborating with researchers under supervision.

Conduct embodied and physical AI research, implement and deploy machine learning algorithms into internal products, collaborate with researchers, and stay current on machine learning developments. Prepare insight and technical reports. The role requires deep learning knowledge and strong Python and PyTorch coding skills; experience with large language models and robotics is preferred.

Develop and maintain software tools and infrastructure supporting machine learning and AI workflows. Build backend services, APIs, automation tools, and integrations; support large-scale experiments, evaluation, and data processing. Debug issues, improve reliability and performance, collaborate with researchers and engineers, gather user feedback, provide technical support, and write clean, tested code.

Develop grid integration, control, and protection technologies for grid-forming and grid-following inverters, converters, and microgrids. Build power-system EMT simulation models, implement algorithms in C/C++ and Python, optimize generated code for real-time simulation, and deploy protocols and algorithms on PLC controllers. The role involves EMTP, PLECS, or Simulink modeling, IBR protection, communication protocols, technical reporting, and support for patents and research publications.

Conduct research and development in computer vision, machine learning, LLMs, and vision-language models. Develop image and video understanding or generation systems, multimodal reasoning and agentic applications, and optimize models for mobile computing constraints. Responsibilities include prompt engineering, model adaptation, fine-tuning, evaluation, and applied AI research.

Leads the propulsion and vehicle fluid systems organization for a medium-lift launch vehicle. Responsibilities include setting technical architecture, driving design through flight and reuse, managing schedules, budgets, risks, suppliers, and certification interfaces, and building a multidisciplinary engineering team. The role requires deep liquid bipropellant rocket engine experience, fluid and propulsion system analysis, component and plumbing design, hazardous operations leadership, test campaign experience, and stakeholder and proposal engagement.

Own the architectural evolution of Robinhood’s core infrastructure across service mesh, Kubernetes compute, and Terraform provisioning. Lead multi-region platform resiliency, diagnose issues at the Kubernetes, etcd, Envoy, and Terraform provider layers, contribute upstream when appropriate, and drive cross-functional architectural decisions. The role requires deep infrastructure expertise, production Go or Python development, and the ability to influence complex engineering organizations.

Architect and develop scalable backend systems, RESTful APIs, asynchronous services, and NoSQL data solutions supporting millions of customers and connected devices. Build quality tools, frameworks, and high-availability systems; conduct architecture design, code reviews, testing, debugging, performance tuning, and feature deployment. Collaborate with Product, QA, and DevOps teams while using AI-assisted development tools to improve coding, reviews, documentation, and system design.

This role focuses on Microservice Architecture and data management strategies for generating pricing requests and optimizing data storage in a fintech context.

The intern will research Physical AI, implement algorithms, write scientific papers, and analyze ML trends in AI. Collaboration with researchers is essential.

The Senior Researcher will develop approaches in Embodied AI, work with generative AI and reinforcement learning, and contribute to top-tier research publications.

The intern researcher will focus on developing LLM models for virtual environments, publishing papers, and contributing to AI/ML research frameworks.

The researcher will focus on advancing AI in computer vision and autonomous driving, implementing generative AI models, mentoring staff, and managing projects. They will also contribute to patent filings and stay updated with industry research.