Top Python Jobs in Toronto

Design, develop, and deploy generative AI solutions (LLMs, RAG, vector DBs, agentic AI) for financial applications. Build AI agents, implement RAG pipelines, fine-tune and evaluate models, collaborate with engineering to productionize models (CI/CD, containers, cloud), and communicate results to stakeholders.

This role leads application system design and implementation, drives collaboration across teams, manages projects, and mentors developers while ensuring risk compliance.

As a Quantitative Researcher, you will conduct quantitative modeling and analysis for evergreen private equity portfolios, support liquidity management, and collaborate on client engagements using large datasets.

As a Staff Software Engineer, you'll build scalable systems for the Tokenization Engine and mentor juniors, collaborating with cross-functional teams to enhance system performance and stability.

As a Forward Deployed Engineer, you will build and ship features for an AI workspace platform, develop autonomous agents, and manage end-to-end deployments, collaborating closely with clients in various sectors.

The Technical Lead will design and implement backend systems, mentor engineers, optimize performance, and manage cloud architecture while ensuring scalable and reliable data processing.

As a Verification Engineer, you will lead the verification of Serdes by developing AMS SystemVerilog models, collaborating with the design team, and ensuring model quality.

Develop and deploy AI solutions for enterprise clients, focusing on large language models and agentic systems integration while ensuring quality, scalability, and security.

The Applied Machine Learning Research Scientist will translate ML techniques into scalable systems, improve LLM performance, and optimize workflows while collaborating closely with researchers and engineers.

As a Senior Data Scientist, you will design AI solutions, lead NLP implementation, and mentor junior staff while transforming data into actionable insights.

Analyze complex datasets, build interactive dashboards, run predictive and statistical analyses, enforce data governance, automate reporting, and partner cross-functionally to deliver actionable insights.

Lead machine-level systems engineering for robotics: derive requirements from deployment targets, define use cases and interfaces, build error/performance budgets, run verification/validation, own safety architecture, support integration, field-commission devices, and drive cross-functional alignment.

Build and own hardware test function for robotic systems: design fixtures and rigs, create test plans, instrument DAQ systems, run environmental and durability tests, diagnose root causes, build reliability models, and automate test reporting to qualify machines for field deployment.

Lead design and implementation of backend services and distributed systems for real-time AI automation. Build scalable, observable microservices, streaming data pipelines, and async event-driven architectures. Collaborate across frontend, product, and DevOps to ensure performance, reliability, and seamless integration at scale.

Design, simulate and validate analog and mixed-signal IC blocks (PLLs, ADCs/DACs, filters, high-speed I/Os). Develop behavioral models (Verilog-A) for top-level simulation, perform process-corner simulations, automate flows with scripting, and validate silicon and system-level lab performance while collaborating with analog leads and multi-site teams.

Founding engineering member building an AI-driven life-sciences SaaS platform. Own features end-to-end from design to production support, drive technical solutions, enforce best practices, perform expert code reviews, and mentor engineers to grow the team and deliver scalable, high-volume products.

Design, build, and productionize agentic systems: agent loops, orchestration, memory, tool integrations, and multi-agent workflows. Improve reliability by diagnosing emergent failure modes, instituting guardrails, and continuously evaluating agent behavior. Optimize tradeoffs among latency, quality, and token cost, and integrate agents with systems of record for business-grade production deployment.

The Associate Consultant will provide analytical support for client projects in life sciences, assist in developing proposals, conduct quantitative analyses, and communicate findings to stakeholders, while working collaboratively in a team environment.

Lead design, automation, and lifecycle management of PostgreSQL environments for high availability, scalability, security, and disaster recovery. Automate provisioning, upgrades, monitoring, and credential rotation; optimize schemas and queries with Product and Data teams; drive multi-region cloud database strategy; act as senior escalation for incidents and root-cause analysis; mentor engineers and document reusable operational patterns to improve reliability and developer productivity.

Develop, deploy, and own RTL-to-GDSII physical design methodology and CAD flows for IP delivery. Automate PPA exploration, document flows, partner with design teams and EDA vendors, qualify new nodes/PDKs and EDA releases, and apply ML/LLMs where they improve flow optimization and scalability.

Design, develop, and maintain scalable Databricks-based ETL/ELT data pipelines and transformations. Support migration from HANA to a modern lakehouse, ensure data quality and performance, troubleshoot issues, participate in code reviews, and collaborate with architects, analysts, and stakeholders to deliver enterprise reporting, analytics, and AI-ready data solutions.

Lead application infrastructure modernization including cloud migrations, container platform administration (OpenShift/Kubernetes/Docker), CI/CD and IaC automation, and development of AI-driven automation. Provide systems analysis, design, implementation, and user support while advising stakeholders and ensuring security and compliance.

Participate in design, development, testing, and support of application systems and scalable ETL data pipelines. Implement Agentic AI automation, debug and secure applications, collaborate with stakeholders, and coach junior analysts while ensuring compliance and data integrity.

Senior full‑stack developer responsible for designing, developing, and maintaining enterprise‑scale React.js frontends and Java (17+) Spring Boot microservices. Modernize Angular apps to React, build REST APIs and event‑driven pipelines with Kafka, integrate SQL and NoSQL databases, support CI/CD and containerized deployments (Docker, Kubernetes, OpenShift), and monitor production systems using ELK/Grafana.

Provide end-to-end technical support for OpenAI products, troubleshooting API failures, integrations, authentication, and production incidents. Own escalations, reproduce issues, analyze logs, and collaborate with Engineering and Product to prevent recurrence. Drive automation and AI-powered tooling to scale operations, and provide occasional on-call holiday/weekend support.