Top Python Jobs in Toronto

Builds secure, automated identity and access management tooling, including access request workflows, self-service APIs and interfaces, user lifecycle pipelines, audit logging, and access review systems. Integrates HR systems, identity providers such as Okta, and security platforms while collaborating with Security Engineering, IT, and platform teams to improve scalable access provisioning, deprovisioning, compliance, and developer experience.

Conduct outbound prospecting to global enterprise businesses, qualify early-stage opportunities, and support strategic account executives. Use GTM tools, automation, research, enrichment, personalization, and sequence testing to improve efficiency. Identify new buyer personas, refine positioning, maintain HubSpot data quality, manage pipeline hygiene, and follow up on events and inbound leads. The role requires curiosity, strong written and phone communication, persistence, disciplined execution, and comfort working without a fixed playbook.

Build and deploy applied machine learning models and data-driven systems that classify, cluster, label, and enrich Internet-observed assets. Develop feature pipelines, training datasets, evaluation frameworks, confidence scoring, and production inference services. Collaborate with engineering, research, security, and product teams to transform raw Internet telemetry into high-quality datasets and customer-facing insights.

Leads MAU analytics and data science, managing decision scientists and data scientists while setting quality standards. Owns MAU driver modeling, forecasting, causal analysis, experimentation, and exploratory work supporting growth strategy. Establishes consistent analytical practices, partners with revenue, product, engineering, and data engineering leaders, and embeds the team in roadmap planning. Promotes AI-native workflows through coding agents, automation, and analytical tools while coaching team members into strategic advisors.

Build, deploy, and operate highly available compute infrastructure for satellite operations and image processing across customer cloud and on-premises environments. Architect air-gapped deployments, manage Kubernetes orchestration, improve reliability and scalability, troubleshoot distributed systems, optimize constrained clusters, document operations, and participate in on-call rotations. Collaborate with internal and external stakeholders to clarify requirements and deliver reproducible, consistently performant services.

Research and optimize AI and machine-learning systems across desktop and mobile platforms. Evaluate model performance, develop and deploy on-device applications and agents, and improve browser ML products. Apply systems and network expertise, collaborate with privacy and security researchers, and investigate AI risks. The role involves open-source development, performance benchmarking, and use of modern ML frameworks to deliver privacy-focused solutions.

Lead end-to-end database migrations from Oracle/SQL Server to PostgreSQL for Guidewire Cloud. Design migration and cutover strategies, optimize performance, build automation and tooling (bash/Python), configure replication tools (AWS DMS, GoldenGate, transactional replication), validate and reconcile data, troubleshoot across application and network layers, and drive repeatable, low‑downtime migrations while collaborating with cross-functional teams.

Design, build, deploy, and optimize production-grade AI systems, including LLM applications, autonomous agents, multi-agent workflows, machine-learning models, data and inference pipelines, and evaluation frameworks. Develop secure, scalable AI services using retrieval-augmented generation, tool calling, orchestration, and model fine-tuning. Monitor reliability, performance, safety, cost, and business outcomes while applying governance, observability, and responsible AI practices.

Build and deploy production-grade AI agent solutions for customers. Responsibilities include identifying automation opportunities, integrating databases and third-party APIs, developing scalable services, rapidly iterating in customer environments, and collaborating with product, research, and engineering teams to shape the platform roadmap.

Design, deploy, and maintain AWS and Databricks data infrastructure, data lakes, and scalable ETL pipelines. Build custom ingestion services and connectors using Airbyte, Go, and Python; optimize performance, reliability, monitoring, and data quality. Implement cloud data governance, security, access controls, encryption, and compliance practices while collaborating with platform engineers, analysts, and stakeholders.

Leads the identification, development, testing, and scaling of AI and automation solutions across internal delivery processes and future customer-facing use cases. Builds automated test suites, scripts repetitive workflows, pilots generative AI and agentic tools, creates reusable automation assets, tracks measurable value, and enables teams through training and knowledge sharing. Collaborates with project managers, product owners, process owners, testing communities, and delivery teams to ensure maintainable, responsible, and broadly adopted solutions.

Build software for renewable energy campuses, including high-fidelity simulations, geospatial data pipelines, automated site and electrical design, and energy management systems. Develop real-time controls, SCADA and telemetry integrations, testing infrastructure, and safety systems for islanded solar and storage facilities. Collaborate with power, civil, and external engineering experts to convert domain knowledge into reliable software and accelerate utility-scale site design and deployment.

Architect, develop, integrate, test, debug, and optimize embedded software for diverse hardware platforms using RTOS, bare-metal, Zephyr, and Linux environments. Lead software architecture, system validation, test automation, and multi-threaded application development while collaborating with hardware and software teams. Define test strategies, analyze defects, document designs, conduct code reviews, mentor engineers, optimize performance and power usage, and contribute to open-source projects.

Deploys, integrates, and scales enterprise generative AI solutions in customer cloud environments. Responsibilities include architecting GCP and Vertex AI infrastructure, deploying and optimizing LLMs, building RAG data and vector search pipelines, managing GPU/TPU workloads on GKE, automating infrastructure with Terraform, and advising clients on AI safety, prompt engineering, hallucinations, and inference costs. The role also collaborates with research and platform teams and requires travel to client sites.

Owner of end-to-end data analysis and delivery for product and client solutions. Design queries, datasets, reports and dashboards, protect recurring data deliverables, partner with Product/Sales/Technology, mentor junior analysts, and apply automation/AI to improve workflows and inform product strategy.

The Data Analyst will analyze large datasets, collaborate with stakeholders, develop data processes, and support data-driven decision-making to improve business efficiency.

Lead design, development, and maintenance of scalable full-stack applications using React, TypeScript, and Python. Define architecture, APIs, CI/CD, and distributed systems. Drive adoption of Claude Code and agentic AI workflows, establish prompt-engineering standards, and implement quality gates for AI-generated code.

Lead design and implementation of full‑stack, cloud‑native applications; analyze complex business and system processes; coach mid‑level developers; drive application architecture, coding standards, testing, and deployment; integrate Gen‑AI capabilities and ensure regulatory and policy compliance.

Productionize, optimize, and scale LLM and ML inference across multi-cloud and Kubernetes. Deploy GPU-based workloads, implement routing/failover for model services, reduce latency via quantization/pruning/distillation, profile and tune hardware utilization, and build observability, monitoring, and cloud-native guardrails for enterprise AI services.

Lead security and compliance architecture for CoCounsel, implementing SOC 2, ISO, HIPAA, and FedRAMP controls; build compliance-as-code, data protection (encryption, key management, tenant isolation), IAM, observability, and audit tooling; partner with security, legal, and engineering; mentor teams and ensure production-scale, provable compliance and incident readiness.

Lead design, build, and operation of cloud infrastructure, CI/CD pipelines, and platform tooling. Implement IaC (Terraform), automate deployments, troubleshoot live systems, maintain monitoring/logging, mentor engineers, set DevOps technical direction, and evaluate new tools.

Lead and grow a team of DBAs and data engineers to ensure reliable, scalable, and secure data infrastructure. Oversee heterogeneous databases, define cloud and containerization strategies, drive IaC and automation, support data pipelines and ETL/ELT, and implement high availability and disaster recovery practices.

Design and deliver scalable backend services for Veeva Ostro's SaaS platform. Architect high-performance APIs, optimize application and database performance, collaborate cross-functionally to ship features, champion code quality and testing, evaluate backend technologies, and troubleshoot live system issues to maximize uptime.

The Senior Data Engineer will scale the data ecosystem, construct data models, build systems for KPI tracking, and ensure data safety.

Build and own marketing measurement, attribution, experimentation, and analytics for performance, influencer, and lifecycle marketing. Responsibilities include creating dashboards, debugging attribution across advertising platforms and CRM systems, designing incrementality and A/B tests, analyzing CAC, ROAS, payback, cohorts, LTV, and channel efficiency, developing attribution taxonomies and instrumentation, and translating findings into recommendations for marketing, product, finance, and executive stakeholders.