Top Python Jobs in Toronto

Lead end-to-end physical implementation of major IP blocks or full-chip designs: floorplanning, place-and-route, clock tree synthesis, timing closure, physical verification, and automation of flows. Collaborate with RTL, DFT, verification, package, and library teams to meet PPA targets, mentor junior engineers, and drive manufacturability and sign-off across PVT corners.

Lead cloud infrastructure monitoring, automate operations, and design AI-driven predictive monitoring and automated incident response. Manage CI/CD pipelines, enforce cloud security/compliance, build monitoring/logging/alerting systems, perform incident triage and collaborate with development teams to optimize cloud resources.

Optimize and scale search applications, implement performance monitoring, develop benchmarking frameworks, and ensure high availability of search services.

Design, build, and deploy scalable ML models and pipelines to enhance a talent marketplace and GenAI solutions. Lead experimentation (A/B tests, statistical validation), improve production ML performance, ensure code and data quality, work with cross-functional teams, mentor junior engineers, and propose innovative AI-driven solutions aligned to business goals.

The role involves statistical modeling, forecasting, and stress testing in banking, utilizing programming tools for analytics and collaborating with teams for data-driven decisions.

Join a cross-functional team to develop data products, write efficient code, influence AI roadmap, and collaborate with diverse professionals.

The role involves designing and developing front-end and back-end components, mentoring team members, ensuring system efficiency, and optimizing platform performance in a collaborative team environment.

Manage a portfolio of clients as primary contact, build trust-based relationships, investigate and resolve data issues, analyse and reformat large datasets for onboarding, collaborate with internal teams to improve onboarding and service, and provide product feedback to help scale processes and automation.

Lead deployment and scaling of AI/ML models, agentic tools, and automation across R&D. Drive MLOps, platform integration, compliance, stakeholder partnerships, capability building, end-user support, and metrics tracking to deliver measurable value.

Lead governance, review, and validation of clinical data deliverables ensuring CDISC/SDTM compliance and submission readiness. Oversee EDC/eCRF design, data quality control frameworks, vendor deliverable review, reporting/visualization, and integration of external data sources. Support scalable data platforms, automation, and AI-enabled capabilities while partnering with Data Management, Statistics, and vendors to ensure data traceability and regulatory alignment.

Senior individual contributor in People Analytics leading workforce analysis, dashboards, data quality, and insight generation to inform HR and business decisions. Partners with talent, engagement, and planning teams to produce scalable analytics, benchmarks, and recommendations.

Four-month, full-time research fellowship focused on ML systems and performance. Fellows build and evaluate infrastructure-heavy projects (e.g., CPU simulators, accelerator backends, large-scale distributed training), use external models/APIs, receive mentorship, funding for compute, and aim to produce public research outputs.

4-month full-time funded research fellowship using external models/APIs to produce public outputs (papers). Fellows receive mentorship, workspace access (Berkeley or London) or remote options within US/UK/Canada, weekly stipend, compute funding, and are expected to implement experiments, collaborate with mentors, and communicate results. Applicants must be fluent in Python and authorized to work in the US, UK, or Canada.

Four-month full-time research fellowship supporting empirical AI safety projects using external models and APIs. Fellows receive mentorship, compute funding, and workspace access to produce public outputs (e.g., papers) across safety, robustness, interpretability, RL, and societal-impact topics.

Four-month full-time research fellowship mentoring fellows to run empirical RL and LLM projects using external infrastructure. Fellows receive compute funding and a weekly stipend, produce public outputs (e.g., papers), and work on RL environments, algorithms, model fine-tuning, and training/evaluation of large models with mentor support.

Lead design and delivery of AI solutions (RAG and agentic architectures) for asset and wealth management clients. Architect retrieval pipelines, semantic models, GraphRAG, and cloud integrations. Manage project planning, governance, budgets, technical handover, and mentor development teams while promoting best practices and responsible AI.

Design and own end-to-end data quality systems for managed AI data studies: define rubrics, sampling plans, automated checks, launch gates, drift detection, dashboards, and calibration. Investigate integrity issues, run root-cause analysis, build automation in Python/SQL, and partner with Product, Engineering, and Operations to embed quality controls, train reviewers, and scale repeatable quality playbooks across programs.

Lead engineering efforts, manage technical teams, ensure software quality, drive automation, and guide product strategies in machine learning security.

As a DevOps Engineer, you will create automation for a new managed service product in AWS focusing on GitOps solutions and ArgoCD.

Drive customer success in AI adoption by managing complex engagements, collaborating with technical teams, and communicating effectively with stakeholders.

The Implementation Analyst will manage client relationships, implement product features, optimize sales processes, and leverage analytics to improve performance.

The Junior Actuarial Analyst supports analysis of claims data, reserve evaluation, actuarial modeling, and financial reporting for the Reserving team.

The Integration Engineer Level III designs and builds APIs, manages data integration services, ensures production readiness, and provides technical leadership while working on complex projects in an Agile environment.

The Data Visualization Developer will create and support dashboards in Power BI, develop SQL scripts, perform regression testing, and troubleshoot existing scripts.

As a Cybersecurity Researcher, you'll analyze malicious packages in real-time, enrich vulnerability data, build AI-driven detection systems, and contribute to original research in supply chain security.