Top Python Jobs in Toronto

Lead and administer on-premises and Azure SQL Server environments including deployment, migration, backups, replication, monitoring, performance tuning, security, troubleshooting, and disaster recovery. Automate DBA tasks, support change deployments, provide after-hours support, and collaborate with architects, developers, and application support teams to ensure availability and reliability.

Design, develop, and deliver full-stack features for e-commerce apps. Convert user feedback into product improvements, maintain and optimize high-traffic back-end systems, perform code and design reviews, and improve development and deployment processes.

Deliver and implement ServiceNow solutions (ITSM/ITOM), configure and integrate products, develop custom scripts, produce technical documentation, run workshops/POCs, and support sales and service growth. Work is consultative with customer-facing delivery, both remote and on-premise.

Deliver ServiceNow consulting engagements focused on ITOM (discovery, service mapping, CMDB, event management); develop custom scripts and integrations; produce technical documentation; support services growth; deliver onsite or remote and educate customers on ITOM/ITIL practices.

Develop and extend data ingestion pipelines for AI model training, manage cloud infrastructure, and collaborate with AI scientists. Bring new audio data sources into the system.

Define technical vision and roadmap for the company ML platform. Architect scalable ML pipelines, MLOps practices, security, observability, and integrations. Guide model training, deployment, serving, monitoring, and provide technical leadership and mentorship across engineering teams.

Analyze, extract, clean, and model large datasets from multiple systems; build data warehouses and predictive models; create financial analyses, dashboards, and client reporting; implement and monitor models with client teams; support client relationships and contribute to proposals and marketing as needed.

Perform end-to-end BI and data analytics work: extract and transform large datasets, build data warehouses and predictive models, create dashboards and reporting, manage client relationships, oversee analysts, and contribute to proposals and marketing as needed.

Deliver financial models, quality of earnings reports, KPI dashboards and data analyses; conduct market and company research; build client-facing decks and tools; manage client relationships and assist with proposals and marketing as needed.

Lead the design and architecture of a Golang-based Software-in-the-Loop simulation platform validating GO device firmware at scale. Own technical initiatives, CI/CD pipeline management, test frameworks, hardware-in-the-loop integration, and virtual-twin tooling. Mentor developers, perform code reviews, define roadmap items, and collaborate cross-functionally to ensure robust, scalable embedded testing infrastructure.

Support and manage AR systems for Revenue Operations: handle bug triage, gather requirements, support implementations, maintain documentation, perform KPI and data analysis, and partner with IT and stakeholders to improve processes and data integrity.

Design, build, and maintain Databricks/Spark ETL pipelines and Bronze-Silver-Gold architectures; implement event-driven streaming with Pub/Sub and Protocol Buffers; prepare datasets for LLM fine-tuning and embeddings; integrate third-party sources (Shopify, Klaviyo); implement attribution, CLV, and analytics models; ensure data quality, monitoring, and idempotent retry-safe pipelines.

Provide technical sales consulting and partner enablement for Google Cloud solutions: assess customer environments, design scalable architectures, prototype integrations/PoCs, support solution evaluations, and ensure sales hygiene in Salesforce.

Design, train, and deploy spatio-temporal and time-series ML models integrating weather and client data. Perform exploratory analysis, optimize model performance using distributed frameworks, own model lifecycle (testing, deployment, monitoring), document technical work, and collaborate cross-functionally to deliver scalable B2B data products and commercial insights.

Lead web and mobile development projects using modern tools and relational databases. Design frameworks, reproduce and resolve issues, enforce unit/integration testing, prepare documentation and deployments, mentor developers, gather requirements, and apply AI across the SDLC.

The Staff Software Engineer, Backend for Capacity Modeling develops scalable backend systems, maintains capacity models, and collaborates on technical strategies while ensuring system availability and high-quality code delivery.

Build and maintain backend systems for money movement and card ledger features. Design, develop, and launch scalable APIs and services (Python or Kotlin) using AWS, MySQL, and Kubernetes. Collaborate with product, design, data science, and cross-functional teams, support operations and on-call, create and monitor metrics, participate in code reviews and hiring, and deliver well-tested, extensible solutions.

Develops and executes models to forecast Pre-Provision Net Revenue for wholesale banking for stress testing and capital planning. Analyzes and reconciles outputs, builds aggregation processes, prepares presentations and narratives, supports governance and controls, drives automation and improvements, debugs model implementations (SAS/Python), and enhances analytics in PowerBI while collaborating with stakeholders across finance, risk, and lines of business.

Lead and deliver complex analytics, machine learning, and generative AI initiatives from problem framing to implementation. Design model strategies, evaluate AI/LLM solutions and agentic workflows, translate results into business recommendations, prepare business cases, mentor junior data scientists, champion Responsible AI and governance, and collaborate with product, engineering, and business partners to drive scaled AI outcomes.

Lead data-driven measurement and performance initiatives for AdTech solutions. Analyze data, design experiments, troubleshoot performance, partner with Product/Engineering/Sales, evaluate revenue opportunities, and support implementation and reporting for measurement solutions.

Design, build, and deploy production-grade agentic multi-agent systems and stateful workflows. Implement memory and vector-based RAG pipelines, secure tool integrations, and cloud-deployed agents. Optimize LLM orchestration, enforce regulatory security and guardrails, collaborate with DevOps/RPA teams (UiPath), and maintain high code quality in Python/TypeScript.

Build and maintain golden datasets and automated evaluation pipelines to audit multi-agent LLM behavior. Trace trajectories, tune prompts and function-calling, optimize tool integrations (APIs, RPA), monitor production drift and hallucinations, and implement guardrails and RAG pipelines to ensure reliable autonomous workflows.

Design and build AI‑enabled full‑stack capabilities for insurance product modeling and content transformation. Implement Java microservices on AWS with Docker/Kubernetes, create performant JavaScript/TypeScript front ends, leverage AI-assisted coding, improve CI/CD and observability (TeamCity, Git workflows), apply enterprise architecture and design patterns, and collaborate with product and engineering teams to deliver secure, scalable SaaS services.

Lead and support pricing and actuarial initiatives for home and auto products, ensuring regulatory compliance, governance, and alignment with business goals. Drive analysis, implementation, monitoring, process improvements, documentation, stakeholder collaboration, and mentoring to enhance pricing impact, retention, and operational efficiency.

Develop, test, and maintain GenAI/ML-based application components; implement new features, unit tests, and fixes; collaborate with stakeholders and tech partners; participate in code reviews, incident management, and continuous improvement; mentor team members and ensure solutions meet performance, security, and governance standards.