Top Python Jobs in Toronto

Partner with the Link product team to analyze data, build statistical and ML models, design and analyze experiments, and produce insights to improve conversion, enable local payment methods, and develop consumer features. Communicate findings, collaborate cross-functionally, and deliver impactful, production-ready analyses and models.

Own and extend the company data platform: model business logic in dbt on BigQuery, maintain pipelines and Airflow orchestration, ensure data quality and cost control, serve metrics via Hasura/Metabase, and deliver documented, tested marts and KPIs for leadership, marketing, and operations.

Support finance operations including channel partner and sales commission accounting, contract/deal desk processing, and operational reporting. Use Excel, SQL/Python, AI tools, and ERP/CRM systems to improve processes, prepare journal entries, coordinate payroll/submissions, respond to stakeholders, and assist audits and onboarding.

Lead end-to-end development of ODAIA's AI-powered commercial intelligence features. Build React/TypeScript frontends, design and operate backend APIs and services, integrate data/ML systems, drive architecture decisions, mentor engineers, and improve testing, observability, and code quality.

Build and lead Clutch's internal developer platform: define platform strategy, architect CI/CD and deployment workflows, design and scale AWS infrastructure with Terraform and GitHub Actions, improve developer velocity via automation and tooling, and establish reusable platform standards for reliability, observability, security, and operational excellence.

Senior Software Engineer to design and implement C++/Python software, accelerate workloads with CUDA, develop and maintain Linux kernel modules and system services, optimize system and GPU performance, manage Linux systems, mentor junior engineers, and integrate AI technologies across products.

Design, build, test, and deliver scalable machine-learning and NLP systems and large-scale data pipelines. Integrate ML models into production, write maintainable tested code, collaborate cross-functionally, and drive research-to-product development in an agile environment.

Build and maintain backend services, infrastructure, and data systems for Robinhood Wallet. Design scalable, secure architectures and implement product-facing features for cryptocurrency and tokenized trading. Improve system performance, engineering productivity, and risk reduction while collaborating with client teams, product, design, and external vendors.

Design, build, test, and deploy scalable backend services and data systems for Robinhood Wallet. Lead architecture and code quality, collaborate with product, client engineers, security, and vendors, and mentor engineers to deliver secure, high-performance crypto trading and custody features.

Design and implement high-performance LLM inference systems and runtime optimizations (vLLM), profile and optimize GPU kernels, benchmark inference performance, integrate research into production-grade open-source software, and collaborate across teams to improve serving efficiency using CUDA, PyTorch, and profiling tools.

Lead organization-wide quality strategy by embedding shift-left testing, TDD/BDD, and AI-driven validation into CI/CD. Define V&V standards for AI outputs, build automated validation gates and human-in-the-loop checkpoints, evaluate AI developer tools, coach teams, and partner with product to ensure testable acceptance criteria and requirements readiness.

Provide strategic guidance and oversight of Finance risk and control programs. Design, assess and test financial reporting and operational controls; develop monitoring, reporting, and key risk indicators; advise stakeholders; update policies and standards; enable data-driven decision making using analytics, scripting and AI; drive process improvements, automation, coaching and cross-functional collaboration to strengthen control effectiveness.

Lead the Canada segment's measurement and insights practice, building measurement frameworks, analytics engineering, and data science capabilities. Manage a team of analysts and engineers, partner with marketing and product leaders, implement Databricks-first architectures, run experimentation and attribution, and deliver executive-ready insights to drive conversion, retention, and channel efficiency.

Lead mechanical engineer responsible for structural and dynamic FEA of reactor pressure vessels and internals, ensuring ASME Section III compliance, producing technical reports, mentoring engineers, and coordinating cross-disciplinary teams for SMR projects under regulatory and quality requirements.

Design, build, operate and improve data pipelines, lakehouse assets and cloud infrastructure (Microsoft Fabric/Azure). Ingest, transform, validate and deliver data from enterprise systems; support observability, troubleshooting, VMs, Docker, source control, and cross-functional product squad collaboration to deliver analytics and application data products.

Build, deploy, and scale AI-powered automations and agentic workflows across multiple retail brands. Connect APIs and platforms, write Python/JavaScript scripts, integrate LLMs and automation tools (n8n/Zapier/Make), train non-technical teams, and expand proven solutions cross-brand to reduce manual work and improve ROI.

Build and maintain scalable data pipelines, dbt models, and warehouse infrastructure to deliver reliable data for analytics and BI. Collaborate with cross-functional teams to enforce data quality, documentation, and governance; monitor pipeline health, investigate and resolve issues, and support data migration and automation efforts.

Design and deploy autonomous AI agents and multi-agent systems to automate clinical trial data cleaning, validation, and analysis. Build agentic workflows, ensure GxP-compliant traceability, deploy on AWS with containerized CI/CD pipelines, integrate vector databases and RAG, and create HITL processes with Data Integrity and Quality teams to meet regulatory requirements.

Technical lead for HR Technology responsible for designing, developing, and supporting Informatica and Databricks ETL, SQL and Python scripting, SSO and FTPS/PGP integrations, vendor SaaS integrations, pipeline monitoring, and providing on-call/after-hours support.

Design, build, and maintain core data pipelines and models for Lyft's Safety and Customer Care platform. Scale processing, tune Spark/SQL/MapReduce jobs, implement data quality systems, enable self-service ETL tooling, and collaborate with product, engineering, and analytics teams to deliver reliable reporting and insights.

Lead a business analytics team to deliver data-driven insights, KPIs, dashboards and AI-enabled solutions. Partner with stakeholders to define strategy, automate reporting, prototype AI use cases, and build scalable analytics products while ensuring data quality and governance.

Design, build, test, deploy, and operate cloud-native, microservices-based software. Implement RESTful APIs, IaC, CI/CD, containers/serverless, and database solutions. Monitor and troubleshoot production systems, apply security best practices, and collaborate with global teams to translate requirements into scalable, reliable solutions.

Manage and administer critical SaaS platforms (Tableau, Freshdesk, Datadog), provide tier-2 product support, triage escalations, build automation and reporting with Python and SQL, maintain runbooks and observability, and coordinate with Engineering, Customer Success, and vendors to improve reliability and incident response.

Architect and lead end-to-end production AI solutions across cloud, edge, robotics, and IIoT. Drive AI strategy, product lifecycle, MLOps, model development, deployment, and optimization. Integrate foundation models, multimodal and agentic AI with robotics, sensors, and digital twins. Ensure security, governance, observability, and operational excellence. Mentor teams, coordinate cross-functional delivery, produce technical/service documentation, and translate innovation into commercial value.

Design, deploy, and maintain cloud-based SaaS environments with Infrastructure as Code, CI/CD pipelines, automation scripting, monitoring, incident management, and security/compliance. Collaborate with architects, developers, and clients to run PoCs, streamline releases, conduct DR/VAPT exercises, produce operational metrics, and mentor junior engineers to ensure high availability and reliable service delivery.