Top Python Jobs in Toronto

As a Fullstack Software Engineer, you'll develop critical applications for Hadrian's FactoryOS, collaborating with teams to enhance manufacturing processes.

Lead a team of cloud engineers to design, implement, secure, and optimize cloud-native landing zones on Azure and GCP. Own IaC (Terraform/Ansible), container orchestration (Kubernetes/Docker), CI/CD, monitoring, cost and security optimization, cross-functional integration, documentation, and mentoring.

12-16 week internship implementing and optimizing GPU/accelerator kernels and custom operators, profiling and improving LLM inference and runtime performance, building benchmarks, fixing regressions, and shipping code to production or open-source AI infra projects.

Build and maintain end-to-end web applications powering sales and operations. Design tools for quoting, scheduling, and fulfillment, integrate AI into products, collaborate on UX, ship high-impact features, and contribute to architecture, deployment, and engineering culture.

The role involves building and scaling growth engineering products, balancing quality and speed effectively, and influencing product direction and AI-driven growth solutions.

Design, build, and operate end-to-end training and inference infrastructure for large language and multimodal models. Improve efficiency (memory, parallelism, kernel optimizations), ensure robust scalable training and RL pipelines, optimize low-latency/high-throughput serving (quantization, caching, speculative decoding), manage multi-GPU and multi-cloud orchestration, and productionize new algorithms with strong observability and reproducibility.

Embed with clients to gather requirements and design AI-driven solutions for fraud and fincrime. Architect, train, evaluate, and deploy custom AI agents and workflows, optimize model performance, establish risk metrics and evaluation pipelines, and collaborate with engineering/product teams to scale into production.

The Director of Epidemiology Pipeline collaborates on virology clinical trials, providing scientific expertise, leading project proposals, and overseeing study management and regulatory compliance.

Build production-grade AI workflows, automations, and agent systems across recruiting, security/compliance, operations, finance, and GTM. Design LLM-powered systems, API integrations with CRMs and workflow tools, and automation that reduces manual overhead and improves enterprise readiness and customer experience.

Build production-grade AI agent systems, automations, and workflows across recruiting, security/compliance, finance, onboarding, CRM integrations, and growth. Implement LLM-powered solutions, API integrations, and operational tooling to improve hiring, sales, and enterprise readiness.

As an ML Engineer at Luma AI, you will design high-performance model serving pipelines, manage GPU resources, and optimize CI/CD for large-scale AI systems.

The ML Engineer will integrate model architectures, optimize deployment workflows, maintain CI/CD pipelines, and ensure reliability of inference services across large-scale systems.

As a Software Engineer in Reliability, you'll architect and manage multi-cloud GPU infrastructure, ensuring performance, security, and scale while debugging complex hardware/software issues.

The Research Engineer will design scalable evaluation systems for multimodal generative AI models, integrating metrics and automated pipelines for model assessment and improvement.

Lead and hands-on build Luma's inference serving platform: architect scheduling, routing, autoscaling, and observability across thousands of GPUs; operate and optimize heterogeneous fleets; ship new model architectures from research to production; own SLOs, cost, incidents, and team hiring/mentorship.

The role involves using AI tools to rapidly develop software, working across product and engineering teams, and owning software projects end-to-end.

Contribute to the reliability and performance of Mithril's GPU orchestration platform through automation, observability, and infrastructure management. Collaborate with the team to ensure scalability across multi-cloud environments while maintaining systems stability and implementing SLOs.

The Research Scientist/Engineer will innovate algorithms for real-time adaptation, optimize ML systems, and ensure impactful product interactions.

The Junior Data Scientist will design and develop data models using Machine Learning and Analytics for trading and compliance in finance.

Design, build, and deploy AI-powered legal applications using LLMs, RAG, and agentic AI. Partner with legal stakeholders to translate workflows, build document ingestion and vector search pipelines, ship production-grade features, implement governance/security controls, and mentor/legal users while aligning solutions with enterprise architecture and monitoring quality and evaluation metrics.

Design, build, and maintain scalable distributed data pipelines and a secure data lakehouse for streaming and batch processing to support real-time analytics, ML, and experimentation. Automate, test, and harden workflows, architect logical and physical data models, build ML model features, and collaborate with product, analytics, and data science teams to turn data into value.

Develop and maintain an AI-driven pipeline to auto-generate, process, and publish real-life and digital quests. Integrate AI frameworks, design scalable automation workflows, analyze user data to improve generation quality, build API integrations, participate in architecture and documentation, test with pytest/unittest, and collaborate with cross-functional teams to validate LLM outputs against real-world data.

Design, build, and deploy reliable, outcome-driven AI systems and agentic workflows that plan, reason, and act across enterprise systems. Integrate LLMs into production, work with structured and unstructured data to ground models in business context, and partner with product to ship end-to-end capabilities.

Design and build end-to-end, enterprise-grade systems that enable AI agents to initiate and complete finance workflows. Own features across backend and frontend, integrate AI/ML models into auditable production systems, ensure scale, security, and reliability, and collaborate with product and customers to solve accounting problems.

Lead design and implement end-to-end features across frontend and backend for a data analytics platform. Build React/TypeScript UIs, backend services (JVM languages/Python/GraphQL), work with Postgres, cloud and distributed systems, collaborate with Product and UX, mentor engineers, improve processes, and adopt new technologies including AI to accelerate development.