Top Python Jobs in Toronto

Lead technical strategy and architecture for a backend search team building highly available distributed systems, recommendations, and discovery experiences. Partner with product, design, and analytics; establish engineering standards, operational processes, monitoring, testing, and on-call practices. Drive major technical initiatives, mentor engineers, communicate technical direction, and support scalable consumer and merchant experiences.

Graduate research interns will own end-to-end projects developing customer world models and proactive intelligence. Work spans representation learning, foundation models, reinforcement learning, agentic decision systems, and evaluation. Tasks include designing methods, running experiments, publishing findings, and potentially shipping models into production to impact customer-facing products.

Architect, build, and operate large-scale relational and distributed SQL database infrastructure. Responsibilities include control-plane automation, provisioning, failover, backups, upgrades, zero-downtime migrations, Kubernetes networking, connection proxy optimization, reliability monitoring, capacity planning, and on-call support. The role also involves technical leadership, roadmap ownership, code quality standards, mentoring, and cross-functional collaboration.

Build and operate scalable AI platform services, internal APIs, and production workflows integrating LLMs and AI tools. Own reliability through observability, alerting, incident response, performance tuning, cost optimization, capacity planning, CI/CD, and infrastructure improvements. The role requires Python backend development, distributed systems, asynchronous processing, cloud infrastructure, infrastructure as code, and cross-layer experience spanning services, data, infrastructure, and AI tooling.

Owns analytics and optimization strategy for advertising revenue across Zynga’s mobile game portfolio. Responsibilities include monitoring performance, diagnosing trends, designing A/B tests, identifying monetization opportunities, partnering with product, analytics, and data science teams, supporting AI and ML models, leading cross-functional initiatives, and mentoring analysts.

Lead end-to-end technical client engagements: discovery, architecture, prototyping, and delivery of AI-enabled solutions. Design system architectures and integrations, analyze client data sources, build proofs-of-concept, guide engineering teams, run workshops, and mentor junior developers and Fellows to deliver production-ready outputs.

Develop and productionize camera and camera-IMU calibration systems for robotics hardware. Build automated calibration stations, implement calibration algorithms, validate accuracy on real hardware, diagnose errors, improve production yield and cycle time, and detect or correct calibration drift in deployed devices.

Owns end-to-end quality assurance for AI-enabled mortgage applications and workflows. Responsibilities include risk-based manual and automated testing across web applications, APIs, integrations, data pipelines, business rules, security controls, and operational processes. The role builds regression suites and CI/CD quality checks, validates AI outputs and guardrails, supports UAT and release readiness, coordinates defect triage, investigates root causes, and improves testability using production telemetry and escaped-defect analysis.

The Associate Financial Accountant reconciles general ledger and bank accounts, reviews employee expenses, processes accounts payable invoices, investigates discrepancies, and assists with month-end financial statements. The role also supports Power BI dashboard creation, system upgrades and testing, vendor and employee inquiries, AML compliance, and special projects. Strong organizational, communication, prioritization, and Microsoft Office skills are required, with Power BI expertise preferred and Python experience considered an asset.

Designs, builds, tests, and improves production AI workflows for residential mortgage underwriting. Responsibilities include RAG, document intelligence, agentic workflows, prompt and tool design, deterministic decision logic, evaluation datasets, observability, security safeguards, and human-in-the-loop review. The role develops Python and SQL services, integrates AI capabilities with mortgage systems, supports UAT and releases, analyzes model quality, and improves solutions through monitoring, feedback, and incident analysis.

Set technical strategy for backend identity decisioning systems, lead major engineering initiatives, and ensure highly available operations. Partner with product, design, and analytics teams; establish coding, architecture, monitoring, testing, and on-call standards; communicate technical decisions; and mentor engineers. Build and scale distributed systems supporting KYC, user lifecycle management, and identity decisions across international markets.

Support development of sensor drivers, firmware debugging, hardware and sensor evaluation, PCB-level validation, and hardware bring-up for spatial intelligence capture systems. Collaborate with software and hardware engineers while gaining hands-on experience in embedded systems, networking, and production testing.

Design and develop embedded sensor drivers, firmware, and high-speed networking infrastructure for multi-sensor data capture. Optimize synchronization, latency, and video transfer while evaluating cameras, LiDAR, ultrasonic sensors, and other hardware. Design custom PCBs and collaborate with software, mechanical, and robotics teams on production-grade mechatronics systems.

ML Engineering Intern supporting real-time markerless motion capture systems. Responsibilities include deploying and monitoring pose estimation models in cloud infrastructure, curating training data, running model experiments, diagnosing failures, and improving evaluation and deployment tooling. The role requires 3D computer vision knowledge, Python, and deep learning familiarity, with opportunities to work on containers, orchestration, model optimization, and robotics middleware.

Support research and engineering experiments in 3D reconstruction, neural rendering, and spatial modeling. Implement and evaluate ML techniques, develop experiment tooling, analyze model outputs, diagnose failures, optimize and integrate promising models into production systems, and document findings. The role requires Python, PyTorch, foundational ML and 3D computer vision knowledge, and in-office work in Toronto without immigration sponsorship.

Develop and evaluate research approaches for 3D reconstruction, neural rendering, and spatial modeling. Implement techniques from research literature, run rigorous experiments, analyze results, and help transition promising models into production through profiling and optimization. The role focuses on classical and neural computer vision methods, including multi-view geometry, monocular depth estimation, NeRFs, and Gaussian splatting.

Support cloud infrastructure for machine learning training and deployment. Responsibilities include provisioning compute, orchestrating training jobs, improving MLOps workflows, assisting with model deployment and testing, investigating reliability, latency, and cost issues, collaborating with engineering teams, and documenting infrastructure tooling.

Design, develop, modernize, and support scalable enterprise applications for TD’s customer and regulatory data platforms. Lead technical design within an agile pod, perform root-cause analysis, assess risks, create solution artifacts, participate in reviews, and provide incident support. Build secure, resilient distributed systems using Java, Node.js, Spring Boot, REST APIs, Kafka, Azure, databases, and scripting technologies while aligning solutions with business, security, and regulatory requirements.

Leads Commercial Banking’s data foundations organization, including data strategy, architecture, modeling, ETL pipelines, data quality, governance, operations, modernization, and business-managed applications. Builds trusted, scalable data assets supporting reporting, analytics, AI, and decision-making. Partners with business, technology, governance, and analytics teams while managing service levels, risk controls, platform improvements, and a high-performing data team.

Build and operate applied AI systems, including LLM integrations, agentic workflows, data pipelines, evaluation frameworks, MCP tools, APIs, and governed content-serving layers. The role emphasizes production reliability, provenance, security, cost and latency management, regression detection, and human-reviewed AI outputs. Responsibilities include cloud deployment, structured content modeling, telemetry, governance, mentoring, and collaboration on AI standards. Strong Python, TypeScript, AWS, API, data pipeline, and production LLM experience are required.

Runs biology and chemistry laboratory protocols, records filmed procedures, maintains detailed experimental traceability, manages materials and equipment, troubleshoots technical issues, and improves laboratory workflows. The role produces reliable scientific datasets for robotics and embodied AI systems and requires hands-on wet-lab, robotics, automation, and scientific communication skills.

Leads the design, development, evaluation, and production deployment of document understanding systems for legal, tax, and accounting content. Responsibilities include semantic chunking, document enrichment, hierarchical classification, entity and citation extraction, knowledge graph construction, LLM post-training, model distillation, synthetic data generation, and evaluation framework development. The role guides architecture and AI strategy, partners with engineering on scalable delivery, influences leadership, and mentors applied scientists and ML practitioners.

Build and operate production applied AI systems, including LLM integrations, agentic workflows, data pipelines, evaluation frameworks, APIs, MCP tools, and governed content-serving layers. Develop reliable extraction and classification agents, model evaluation harnesses, telemetry, and structured data pipelines. Ensure security, privacy, provenance, reliability, latency, and cost controls while mentoring engineers and contributing to AI governance and standards.

Lead pricing modeling and experimentation to optimize margin, conversion, and retention. Build elasticity and willingness-to-pay models, run causal and bandit experiments, decompose merchant economics, and develop agentic deal tooling. Own end-to-end data pipelines, ETL, monitoring, and visualization. Evaluate AI systems for accuracy, bias, and drift, and partner with cross-functional teams to translate results into pricing strategy and automation.

Design and implement FPGA code for satellite digital payloads, including DSP algorithms, software-defined radio modulation and demodulation, and embedded processor interfaces. Develop custom IP, improve DSP and interface reliability, integrate vendor IP, and support communications architecture and spacecraft design studies. Participate across simulation, synthesis, place and route, timing closure, and hardware testing using Xilinx FPGAs and industry-standard HDL and simulation tools.