Top Python Jobs in Toronto

Leads digital water projects involving data management, collection, processing, analytics, modeling, visualization, GIS, and custom application development. Supports software selection, procurement, planning, design, and operational activities for water and wastewater utilities. Collaborates with technical teams and clients, communicates analytical results, and stays current with digital water technologies.

Build and operate a scalable data platform supporting warehousing, orchestration, business intelligence, governance, and agentic workflows. Develop Python services, Terraform infrastructure, and developer tools for petabyte-scale data. Partner with data practitioners and product teams, establish security and reliability patterns, set technical direction, improve engineering standards, and mentor engineers.

Build and maintain mission-critical wealth management systems for SMB clients. Design data pipelines, ETL/ELT processes, data models, warehouses, analytics, and reporting solutions using AWS, Snowflake, Mage AI, and other big data tools. Collaborate with data scientists and analysts on predictive models, statistical analyses, and machine learning algorithms. Develop software with Next.js and Python while working closely with the team and clients on financial-domain challenges.

Owns production AI systems end to end, including evaluation pipelines, agents, retrieval, routing, model selection, data feedback loops, and observability. Diagnoses failures across audio, prompts, models, and infrastructure; improves quality through experiments and production debugging; and leads safe rollouts. The role establishes applied AI engineering standards, translates clinical problems into measurable plans, and delivers reliable systems used by healthcare clinicians.

Lead hands-on software development, technical design, and architecture for cross-functional, fault-tolerant applications. Own technical standards, high-level design, engineering best practices, developer experience, and lifecycle delivery. Provide technical guidance to stakeholders, improve internal frameworks and tools, and mentor junior and intermediate engineers. Collaborate within an agile team across the full Software Development Life Cycle.

Evaluate, structure, and price consumer asset-backed transactions; develop capital structuring, pricing, and quantitative loan performance models; and provide insights supporting funding strategy and merchant pricing. Collaborate with Capital Markets, Treasury, Credit, Commercial, Product, Engineering, and other teams to guide funding, product, and business decisions.

Build and own Snout’s data foundation, including PostgreSQL and dbt warehouses, ingestion pipelines, dimensional models, data quality, documentation, and reliable rebuilds. Reconcile data from veterinary practice-management systems, support LLM/AI tooling, translate stakeholder needs into technical plans, and establish the foundation for a future data team and analyst.

Develop and maintain Python-based image-analysis workflows for registration, detection, background subtraction, drift correction, and response measurement. Validate accuracy and repeatability using controls and regression tests, align ultrasound with MRI and anatomical references, and integrate methods with acquisition and reconstruction systems. Optimize processing for large datasets while providing documented tools scientists can use independently.

Develop and maintain shared computational imaging software that converts ultrasound data into image series. Build and optimize beamforming, filtering, motion estimation, and reconstruction methods for real-time and large-scale processing. Validate performance through benchmarks, regression tests, uncertainty analysis, and reproducible experiments. Improve GPU and memory efficiency, establish device requirements, and evaluate learned imaging methods while collaborating with scientists and engineers.

Build and maintain Quora’s machine learning platform and distributed model-serving infrastructure. Develop scalable systems for recommendation and language models, optimize GPU serving latency, throughput, and cost, improve ML tooling and feature stores, and contribute to platform modernization. The role includes production deployment, collaboration with senior engineers, mentoring, and participation in an on-call rotation.

Develop and enhance highly available, scalable, fault-tolerant IAM services on Akamai’s Compute Platform. Design resilient software, build tools for seamless deployment and operation, improve IAM features and customer experience, and research emerging technologies. The role requires extensive Linux software development, Python or Java expertise, secure software delivery, IAM knowledge, and experience with enterprise tools including Git, JIRA, and Jenkins.

Provide technical ownership for Premium Support customers by troubleshooting complex API, integration, authentication, performance, and production issues. Analyze logs and system behavior, reproduce failures, coordinate incident response, communicate with technical and executive stakeholders, and drive postmortems and corrective actions. Proactively monitor customer integrations, develop runbooks and automation, identify reliability risks, and translate recurring issues into product and engineering improvements.

Build, test, secure, deploy, and support Oracle Fusion Cloud technical objects across integrations, reports, extracts, extensions, security, and data processes. Develop Oracle Integration Cloud orchestrations using REST, SOAP, FBDI, and business events; create BI Publisher and OTBI reports; write SQL and PL/SQL; execute comprehensive testing; resolve defects; support cutover, hypercare, month-end close, monitoring, documentation, and knowledge transition.

Own identity and endpoint security across the company, including SSO, MFA, access provisioning, access reviews, MDM, EDR, device security baselines, and IT workflows. Respond to identity and endpoint incidents, assess vendor and SaaS integration risks, support secure AI tool adoption, automate security processes, and help develop scalable security policies and controls.

Leads multiple Fraud Operations teams focused on disputes and compliance. Responsibilities include developing people leaders and individual contributors, setting operational strategy, improving productivity and quality, managing service levels and queue health, resolving complex risk events, driving cross-functional alignment, and implementing scalable process improvements. The role requires significant fraud operations and people leadership experience, strategic planning, change management, AI-enabled efficiency initiatives, and continuous improvement expertise.

Leads enterprise DevOps and cloud infrastructure strategy, building CI/CD pipelines, Infrastructure as Code, automation, observability, and secure software delivery platforms. Partners with engineering, quality, and product teams across development through production environments. Supports disaster recovery, security-by-design, reliability testing, troubleshooting, and operational improvements. Mentors engineers and drives DevSecOps, SRE, and platform engineering maturity across a global organization.

The Applied Scientist will develop quantitative models to improve pricing, demand forecasting, and risk management, collaborating with cross-functional teams to implement solutions.

As an Applied Scientist, you will push the limits of AI/ML in home valuation, tackling diverse ML challenges and optimizing decision-making with data.

As a Data Scientist at Opendoor, you'll enhance pricing strategies through statistical models, machine learning, experiments, and interdisciplinary collaboration to drive business outcomes.

Build and deploy LLM-powered features for clinical, patient, and operational workflows. Responsibilities include prompt design, retrieval, tool use, agent orchestration, evaluation harnesses, feedback loops, production operations, and AI engineering tooling. Partner with clinical, product, and safety stakeholders to ensure responsible healthcare-grade AI. Mentor teammates, communicate model behavior clearly, and stay current with emerging AI research and development practices.

Own the technical design and delivery of multi-component AI systems, including evaluation frameworks, data pipelines, feedback loops, model-tool boundaries, and agent harnesses. Ship reliable LLM-backed features, optimize latency and cost, support APIs and SDKs, review designs and code, and participate in 24/7 on-call rotations. Collaborate across teams on geospatial, navigation, platform, and developer-focused AI problems.

Own regulatory analytics and reporting by building audit-ready datasets, pipelines, dashboards, compliance metrics, and automated workflows. Analyze complex data, monitor quality, support audits and regulatory exams, and deliver actionable insights to compliance teams and leadership. Translate regulatory requirements into accurate reports using Python, SQL, dbt, and Airflow while partnering cross-functionally to manage data issues and remediation.

Leads AI engineering strategy across clinical, patient, and operational products. Designs and operates production retrieval, orchestration, agentic, and evaluation systems, establishing standards for AI safety, observability, responsible deployment, and reliability. Partners with clinical, product, and executive leaders on the AI roadmap, mentors engineers, evaluates emerging models and tools, and codes regularly in Python.

Design scalable human-data solutions for frontier AI clients, translating ambiguous model-training and evaluation needs into executable programs. Lead discovery, methodology, task and workflow design, feasibility estimates, expert profiling, quality strategies, and technical architecture in partnership with engineering and project teams. Advise on fine-tuning, RLHF, benchmarks, red teaming, multimodal data, coding tasks, and agent environments while guiding pilots through early delivery and developing reusable best practices.

Own growth marketing for an AI systems integrator by translating engineering work into compelling stories, videos, demos, and written content. Manage and measure channels including LinkedIn, YouTube, and X; run experiments against pipeline outcomes; and build lightweight tools, dashboards, scrapers, and microsites. The role requires strong writing, genuine AI interest, working-level Python or TypeScript skills, and comfort using AI coding tools. Candidates may be early-career and must be in New York or San Francisco or willing to relocate.