Top Python Jobs in Toronto

Lead end-to-end delivery of AI solutions for Risk, Legal, Procurement, and Compliance, focusing on fraud/financial-crime detection. Shape roadmaps, manage multidisciplinary teams, perform hands-on AI engineering and prototyping, ensure security, governance, model risk and responsible AI, and drive enterprise integration and adoption to realize measurable business outcomes.

Build, optimize, and maintain production data pipelines using SQL, dbt, Python, and PySpark. Own data quality testing, workflow monitoring, alert management, failure debugging, schema drift handling, and CI/CD deployment. Transform large-scale datasets in a Databricks Lakehouse environment while ensuring reliable performance and data integrity. Clearly communicate technical issues, root causes, resolutions, and action plans to technical teams and business stakeholders.

Develop and maintain end-to-end full-stack web and mobile features for MaintainX’s maintenance management platform. Responsibilities include designing customer workflows, solving complex scalability and offline-first challenges, shaping architecture for new teams, collaborating with product and design, owning system reliability, reviewing code, mentoring developers, and improving testing and delivery practices. The role requires participation in on-call rotations and ownership of a functional domain within six months.

Develop and evolve shared platform services, APIs, developer tools, design-system components, and deployment infrastructure. Deliver full-stack features from planning through production, improve development speed, security, reliability, testing, and release practices, and own the long-term health of functional domains. Collaborate with product, design, and engineering teams, review code, mentor developers, support adoption, and participate in on-call rotations.

Leads technical direction for Everand’s backend platform, including architecture, reliability, observability, CI/CD, databases, queues, and scalable distributed systems. Partners with product, design, analytics, web, mobile, and ML teams to deliver personalized reading and listening experiences. Mentors engineers, drives architecture reviews and modernization efforts, improves technical quality, and owns platform health, performance, cost, and resilience.

Develop 3D civil infrastructure models for roads, bridges, earthworks, utilities, and heavy civil projects. Produce construction drawings, quantity takeoffs, volume calculations, and project deliverables. Coordinate models with engineering, surveying, and construction teams; resolve discrepancies; conduct clash detection; integrate point-cloud data; and manage digital documents, model controls, and version tracking.

Build and maintain streaming and batch data pipelines, data lakes, warehouses, and transformation systems using AWS and modern data tools. Collaborate with engineers on data integrity, testing, validation, documentation, and production code. Develop prototypes for uncertain technical solutions, support data visualization infrastructure, lead projects independently, advocate for trustworthy data, and mentor junior engineers.

Designs and automates hardware and software tests to validate recording quality, performance, recovery, and release readiness. Tests long-running sessions and fault conditions, analyzes recorded data for timing errors and corruption, reproduces intermittent failures, isolates root causes, and creates regression tests. Builds physical test fixtures and defines qualification checks across hardware and software configurations.

Designs, builds, and maintains scalable Python applications and cloud-native infrastructure. Responsibilities include managing CI/CD pipelines, OpenShift and Kubernetes deployments, automation, testing, monitoring, troubleshooting, release management, and performance optimization. The role collaborates across development and operations teams, mentors junior colleagues, defines DevOps standards, and manages risk and compliance.

Own the Business Intelligence domain by building scalable data models, dashboards, reports, data pipelines, and actionable insights. Partner with Product, Sales, Operations, Data Engineering, and leadership to improve data quality and decision-making. Transform large datasets using SQL and scripting, conduct experiments, develop predictive models, improve analytical infrastructure, and mentor colleagues.

Develop and deploy predictive and generative AI models for Business Banking use cases, including agentic AI, LLMs, pricing, and anomaly detection. Translate business needs into analytical solutions, define success metrics, evaluate and monitor models, conduct A/B testing, document results, and ensure fairness and stability in production. Communicate technical findings to stakeholders and apply current machine learning research to deliver measurable business impact.

Develop and deploy AI assistants, autonomous workflows, and automation solutions for enterprise risk management. Responsibilities include identifying opportunities, building reusable solutions, integrating approved data sources and platforms, managing the full solution lifecycle, implementing responsible AI controls, monitoring reliability, documenting systems, training colleagues, and measuring business outcomes. The role collaborates with technology, cybersecurity, privacy, compliance, data, and AI governance teams.

Build and ship LLM-powered and agentic features across a SaaS product, including conversational experiences, document understanding, maintenance guidance, and contractor matching. Integrate model APIs and agent frameworks using Python and TypeScript, own features from design through production monitoring, and establish testing and evaluation practices for LLM behavior. Collaborate with product and engineering teams to identify and deliver valuable intelligent capabilities.

Designs and owns the production platform powering AI agents and document-processing accelerators. Responsibilities include orchestration, retrieval, model routing, evaluation, observability, inference optimization, reliability, governance, and cost management. The role develops scalable services and APIs, supports legal and regulated workflows, improves system quality and performance, and provides technical leadership through architecture, code reviews, mentoring, and cross-functional collaboration.

Develop and deploy machine learning and statistical models for commercial property and casualty insurance pricing. Responsibilities include transforming large datasets into insights, building claims and pricing models, managing the full model lifecycle, monitoring performance, improving reproducibility, maintaining data-mining tools, and communicating recommendations to business and technology partners.

Develop and monitor advanced actuarial pricing models for commercial property and casualty insurance. Analyze loss costs, customer demand, portfolio shifts, and emerging segment behavior, then communicate recommendations to business stakeholders. Collaborate with data scientists, underwriters, and actuaries while supporting model validation, innovation, continuous improvement, and mentoring. The role requires Python proficiency and familiarity with SAS and VBA.

Develop and debug embedded Linux firmware for camera and sensor recording systems. Responsibilities include board bring-up, reliable data paths, performance and power optimization, recovery from interruptions, field-failure reproduction, and validation across hardware configurations. The role requires strong C or C++ skills, Python or shell scripting, Linux systems knowledge, embedded ARM experience, concurrency and resource profiling expertise, and experience creating reproducible releases and realistic hardware tests.

Build and integrate robotic hardware and software for repeatable experiments, data collection, demonstrations, and learned-policy deployment. Develop calibration and diagnostic tools for coordinate frames, timing, and sensor quality. Create recording, teleoperation, and evaluation workflows while debugging failures across software, electronics, sensors, and mechanics. Improve system reliability through software enhancements and recovery procedures.

Train and evaluate computer vision models for embedded deployment, build efficient C++ inference pipelines, and optimize latency, memory, power, and sustained performance. Integrate models with embedded Linux, test on representative hardware and data, and investigate errors across preprocessing, inference, and system integration. Lead candidates will set architecture and evaluation standards while guiding model and software development.

Build and maintain frontend and backend components for a rapidly scaling legal-tech platform. Develop APIs and backend systems in Go, implement React/TypeScript user interfaces, optimize performance and security, write tests and CI/CD pipelines, perform code reviews, mentor junior developers, and collaborate with Product and Design in an agile environment.

Lead enterprise client reporting and manage Proof’s data team. Own report accuracy, delivery, client relationships, data pipelines, shared models, BI tooling, and internal data insights. Coach team members, guide technical decisions, review SQL and data models, partner with Engineering and Product, resolve reconciliation issues, and improve automation. The role will establish data quality standards and help the company use trusted data to support growth, internal tools, and AI systems.

Architect and develop scalable Python backend systems for financial risk and intelligence platforms. Apply Generative AI, prompt engineering, token optimization, and RAG to analyze multimodal financial communications and derive trading and risk insights. Build resilient APIs on Kubernetes, research emerging LLM technologies, and collaborate with quantitative, product, risk, and compliance teams. Responsibilities include testing, code reviews, CI/CD, system documentation, and production deployment at global enterprise scale.

Own complex backend initiatives from architecture through production deployment and ongoing evolution. Design scalable services, APIs, data models, asynchronous workflows, and cloud-native systems. Provide technical direction, coordinate dependencies, mentor engineers, and improve testing, CI/CD, observability, reliability, security, and code quality. Collaborate with Product, Design, QA, SRE, platform, and engineering teams to deliver durable customer-focused solutions.

Build and maintain shared platform services, developer tools, APIs, design system components, and release infrastructure. Ship features end to end, collaborate with product and design, improve reliability and delivery practices, support internal engineering customers, review code, mentor developers, and participate in on-call rotation. The role requires full-stack web or mobile development using TypeScript, React, Node.js, and related technologies.

Build and maintain full-stack workflows for scheduling, inventory, reporting, work execution, and technician experiences. Ship features from planning through production, collaborate with product and design, own system reliability and performance, review code, mentor developers, and improve testing and delivery practices. The role involves mobile-first development, large datasets, offline behavior, multi-site scale, and on-call rotation.