Top Python Jobs in Toronto

Build and productionize LLM-powered and agentic AI systems (RAG, fine-tuning, prompt engineering) and web app integrations. Lead design, set best practices, monitor and iterate on performance, mentor engineers, and partner with business and governance to deliver scalable, reusable AI solutions in cloud environments.

Lead and grow the data engineering function, driving Snowflake migration and EDW modernization. Deliver scalable, secure batch and real-time data platforms, embed MLOps/DataOps, CI/CD, and IaC, enforce PCI DSS and data quality, manage onshore/offshore teams, and partner with architecture, governance, security, and product stakeholders to meet enterprise data needs.

Lead and mentor multiple Agile software teams, own technical design and architecture, drive end-to-end delivery, champion AI-first innovation, ensure high-quality releases, partner with product, improve team performance and operational excellence, and communicate with customers and stakeholders.

Senior Developer/SRE will lead technical components, design and write object-oriented code, manage CI/CD (LightSpeed) pipelines, troubleshoot production issues, collaborate on shared codebases, apply networking/REST API/database/CLI knowledge, ensure software quality through reviews and testing, and mentor junior engineers.

Design and maintain ETL/ELT pipelines and semantic/analytical data models; extend metric layers for BI and LLM/RAG-driven natural-language analytics; apply AI/ML and data-science techniques to produce trusted investment metrics, insights, and recommendations; embed data quality, lineage, and governance; collaborate with investment, finance, and technology stakeholders to prototype and productionize AI-enabled reporting solutions.

Develop and train conditioned policies and MARL systems to simulate realistic driving behaviors, implement safety-constrained RL algorithms, design rewards and evaluation metrics, optimize large-scale training pipelines, advance neural architectures for long-horizon planning and spatial reasoning, and integrate research models with production simulation and planning teams.

Design and implement automated data quality frameworks and tests for BigQuery-based pipelines. Collaborate with data engineers and product to define data contracts and quality gates, build observability and anomaly detection, validate complex ELT/ETL processes, and integrate data tests into CI/CD workflows. Drive improvements in documentation, governance, and pipeline reliability.

Lead design and implementation of automated data quality frameworks and monitors for BigQuery pipelines. Collaborate early with data engineers and PMs to define data contracts, build tests in Python/SQL, integrate data tests into CI/CD, and improve data governance and observability for ETL/ELT workflows.

Serve as a client-facing solution architect for Coveo's AI relevance platform, translating business needs into scalable search, recommendation, and generative AI solutions. Lead solution design, architecture, implementation, stakeholder alignment, governance, agile delivery, and documentation across cloud and enterprise ecosystems.

Lead architecture and core runtime foundations for a distributed scanner platform, driving reliability, observability, performance, and engineering rigor while collaborating with hardware and ML teams and mentoring engineers.

Lead EPIC SoC architecture from MRD to PRD, owning digital and high-speed I/O (SerDes, UCIe/PCIe/Ethernet). Integrate analog, photonics, memory, and packaging inputs, drive PPA trade-offs, vendor IP selection, modeling, and cross-functional alignment through product sign-off.

Lead and grow a remote AI engineering organization, manage ~30 forward-deployed engineers, maintain technical standards for agentic full‑stack applications, review architectures, run performance management and hiring, support client engagements, and drive team enablement, evaluation harnesses, and MLOps practices.

Founding research hire to develop clinical reasoning and computer-use models using proprietary hospital and clinic data. Own end-to-end training and evaluation pipelines, design benchmarks exposing LLM weaknesses on clinical reasoning, run experiments, and publish technical reports and papers. Collaborate closely with founders and deploy research into products that improve physician workflows.

Conduct research and implement LLM-based agent architectures for planning, reasoning, and decision-making. Explore agent memory, reflection, self-evaluation, and continual learning. Survey literature, run experiments, evaluate results, and communicate insights with the team.

The Senior Researcher will develop Physical AI research, focusing on robotic models and multimodal learning while collaborating on experiments and publications.

Design and develop AI agents using large language models, optimize multi-agent systems, and integrate these agents into real-world tools and systems.

As a Customer Engineer, you'll bridge technical problems and client needs in analytics and ML, designing data solutions and ensuring high-quality feature delivery.

The Customer Engineer will bridge technical challenges and client needs through full-stack development, enhancing customer experiences and delivering innovative solutions.

The Associate Product Manager will work with analytics, ML, and product teams to develop features based on data insights, ensuring effective data management and customer outcomes.

The AI Engineer will design, develop, and deploy AI solutions in property and casualty insurance, focusing on claims processing, underwriting, and customer engagement while ensuring responsible AI practices and effective data integration.

Coordinate technical work in the team, ensure timely project delivery, and manage cloud server environments including AWS, Azure, and Openstack.

Develop and commercialize firmware for neural network processing on ARM-based processors. Design embedded software for real-time processing, manage buffer interrupts, and optimize compilers.

Design and implement scalable ETL/data pipelines using Python and Airflow; collaborate with technical and non-technical stakeholders to define requirements; build internal tools; mentor and lead small engineering pods; ensure reliable integration architecture and database schema/performance optimization; explore and apply AI technologies to enhance the platform.

The Consultant will conduct financial analyses and modelling, manage client relationships, oversee junior staff, and perform market research. Responsibilities include developing financial tools and ensuring quality control on deliverables.

As a Consultant, you will conduct due diligence, analyze financial statements, develop reports, create financial models, and manage client relationships, ensuring high-quality deliverables to clients.