Top Python Jobs in Toronto

Design, build, and operate scalable Generative AI systems and RAG pipelines; own end-to-end AI application lifecycle on Databricks and AKS; integrate LLMs with data sources and APIs; implement LLMOps, evaluation, observability, and production monitoring; mentor engineers and influence product roadmaps.

The Senior Customer Support Consultant will assist clients with optimization, risk analysis, and product training, collaborating with sales and providing specialized guidance. Requires problem-solving skills and relevant educational background.

The role involves building scalable AI solutions, enhancing productivity through agentic automations, and integrating LLMs and other advanced AI frameworks.

As a Senior Data Engineer, you will build a data platform, create data pipelines for market and trade data, and collaborate with traders and quants to enhance analytical workflows.

Lead and manage teams to design, build, and deploy AI/ML systems with emphasis on LLMs, RAG, NLP, and MLOps. Drive technical strategy, resource and budget planning, standards, risk assessment, and cross-functional influence while ensuring compliance and supervisory accountability.

Lead enterprise Generative AI strategy and engineering: select and deploy LLMs, design RAG and agentic systems, build production GenAI services, establish governance, observability, cost controls, and reusable accelerators while managing senior engineering teams and cross‑functional stakeholders.

Lead initiatives to foster engineering excellence, drive measurable improvements, and manage multiple programs while remaining technically active in coding and design discussions.

As a Staff Full Stack Developer, you will lead technical strategy and oversee both frontend and backend developments, ensuring integration and performance of Dialogue's ServiceOS while mentoring the engineering team.

Embed within the M&A team to identify, prioritize, prototype, and deploy AI and data-science solutions that speed deal sourcing, diligence, pricing, and integration. Architect the data foundation, translate between business and technical teams, build ROI-backed use cases, ship prototypes into production, drive adoption, and measure model performance, time saved, decision quality, and dollar impact across the transaction lifecycle.

Design, develop, and maintain Amazon Connect contact flows and supporting AWS serverless services. Build integrations with enterprise systems (Guidewire, CRM), implement monitoring and incident response, develop CI/CD and IaC, drive automation and AI features, mentor junior staff, and improve contact center reliability and observability.

Lead design and modernization of patient-facing backend services, driving API-first and event-driven architectures on AWS. Improve reliability, observability, security, and scalability of communication pipelines (email, SMS, notifications). Mentor engineers, enforce API contracts, reduce tech debt, and partner with cross-functional teams to build secure systems handling sensitive patient data.

Lead a team to build scalable risk analytics, reporting, and data quality solutions. Translate business needs into technical analytics, ensure governance and regulatory compliance, engage stakeholders, and drive automation and continuous improvement of data processes and model monitoring.

Design, deploy, and operate large-scale distributed systems. Operate Kubernetes clusters and Istio, automate workflows with Go/Python/shell, build observability with Prometheus/Grafana/Loki, troubleshoot networking/storage/performance, support AI/ML infrastructure, and participate in on-call rotations and postmortems to improve reliability.

Lead cloud cost visibility, forecasting, and optimization across AWS, Azure, and AI environments. Build and automate FinOps tooling and workflows, manage tagging and cost allocation, recommend and track savings plans/reservations, monitor anomalies, and collaborate with engineering and finance to drive cost efficiencies.

As an Agentic Data Specialist, design and manage data systems for AI agents, ensuring seamless integration and collaboration across enterprise technologies.

Lead technical direction and implementation of a large-scale AI model serving platform. Design, build, and operate distributed systems (Ray/Ray Serve), ensure scalability, reliability, monitoring (Prometheus), CI pipeline robustness, and evolve the production model registry while collaborating with ML engineers and stakeholders.

The Distillation Lead will define and implement strategies for model distillation and compression, collaborating with various teams to deliver efficient models for real-time systems and simulations.

Design and develop Waabi's observability stack, optimize performance, build automation tooling, and support application requirements while leading projects and mentoring teams.

Develop and maintain production-quality software for self-driving technology. Collaborate with teams, lead discussions, and mentor engineers.

The Software Engineer will focus on ML Ops, developing deep learning models, creating redundancy systems, and generating performance diagnostics, ideally with a robotics background.

Senior DevOps/Cloud Engineer to design, build, and support cloud infrastructure (primarily AWS), implement IaC (Terraform), configuration management (Ansible), manage OpenShift ROSA clusters, design CI/CD and GitOps pipelines, embed security and observability, lead incident response and on-call, and mentor junior engineers.

Manage client onboarding and relationship coordination for buy-side and institutional clients across TD Securities. Improve processes, support front-office desks, ensure regulatory, credit, AML/KYC and documentation requirements are met, track client status, escalate issues, run stakeholder pipelines, and identify automation/technology improvement opportunities to increase operational efficiency.

Own features end-to-end: discover, design, build, and measure scalable frontend/backend systems. Influence architecture, APIs, schemas, performance, and developer experience while using AI tools to accelerate development and improve quality.

Lead Credit Cards analytics and AI initiatives: design, build, deploy, and maintain ML models and analytics assets; drive data-driven product, pricing, and campaign decisions; present insights to senior leaders and ensure measurable business value.

Senior staff individual contributor who architects, builds, and scales production Generative AI and LLM-powered systems and agents. Leads technical strategy, design reviews, model integration, evaluation, deployment, observability, and operational excellence across cross-functional teams while mentoring engineers and shipping high-impact AI features at ecommerce scale.