Top Python Jobs in Toronto

The AI/ML Engineer will design and develop AI-powered applications, automate workflows, and integrate AI into BPM's daily operations, ensuring they deliver business value.

Own and scale the Nx-based monorepo, build system, and CI/CD to make builds, tests, and developer workflows fast, reliable, and observable. Build developer tooling, local dev stacks, and production-grade developer infra with SLOs, on-call, and measurable DX improvements.

Lead pre-silicon emulation strategy for a next-generation AI inference ASIC using Cadence Palladium. Architect multi-rack models, enable software left-shift via hybrid emulation, verify high-speed interfaces and memory hierarchies, perform power/performance analysis, and collaborate with RTL, DV, software teams and Cadence R&D to ensure silicon readiness.

As a Machine Learning Engineer/Scientist, you will develop ML systems for cryopreservation research, manage data pipelines, and deploy models for scientific insight.

As an engineer on the hibernation team, you will develop hardware and software for cryopreservation systems, focusing on mechanical and electrical design.

Senior Geophysicist responsible for compiling, processing, and interpreting geophysical data to support AI-driven drill targeting. Collaborates with data scientists to integrate geophysical insights into predictive models, troubleshoots data issues, and contributes to methodology development and cross-disciplinary projects to improve exploration decision-making.

Provide real-time, text-based mentoring and feedback for middle and high school students preparing for math contests and STEM classes. Answer questions, give hints, and encourage students during live weekly classes (Sundays 7:20–9:00 pm ET). Assist with contest-focused and regular subject classes in math, Python, physics, and chemistry.

Build and scale ML-optimized HPC infrastructure, manage Kubernetes-based GPU/TPU superclusters, optimize for AI/ML training, and mentor teams while innovating in ML infrastructure.

The Forward Deployed Marketing Data Scientist will work with AI customers and engineering teams to optimize AI-driven marketing campaigns through data analysis, diagnostics, and communication of insights to stakeholders.

The AI Strategy Consultant will drive marketing strategy using AI, work with teams to implement solutions, and enhance customer outcomes.

Lead the quality engineering efforts for Replicant's AI platform by defining standards, improving testing strategies, and mentoring a QA team to ensure high-quality outputs across software systems.

The AI Architect will design enterprise-grade AI solutions using Generative AI, LLMs, and orchestration frameworks, focusing on building scalable systems and developing production-ready applications.

Design, build, and deploy cloud-native frontend and backend applications integrating Generative AI and LLMs. Develop APIs/microservices on AWS, implement data engineering with Databricks/PySpark, and use containerization and CI/CD for scalable, secure solutions. Collaborate with product and engineering teams and drive best practices in AI and cloud architecture.

Lead design, build, and scale of secure, multi-tenant Kubernetes infrastructure and CI/CD systems. Own AI tooling infrastructure and MCP servers, implement GitOps and IaC, run streaming analytics (Kafka, Flink, ClickHouse), improve observability and SLOs, lead incident response and postmortems, and mentor engineering teams on reliability, automation, and progressive delivery strategies.

Build and ship AI-driven GTM systems: outbound lead engine, inbound/lifecycle automations, AI-assisted content pipeline, data/reporting layer, and fast production patches to eliminate manual marketing workflows.

Design and implement advanced generative AI models, optimize deployment in production, collaborate with teams, and stay updated on AI advancements.

The Revenue Operations Analyst will manage revenue analytics for publisher accounts, create reports, identify growth opportunities, and collaborate with teams to optimize monetization strategies.

Develop and maintain the Keycard Agent SDK, ensuring compatibility with various languages and frameworks, while engaging with the developer community to enhance agent applications.

As a Full Stack Engineer, you'll own the development of features from design to production, collaborate with various teams, and continuously improve the platform by solving technical challenges.

As a Senior Software Engineer, you will lead your team in delivering features according to specifications, ensuring scalable technical decisions, and mentoring team members.

The Principal Developer will lead the technical direction of the Exposure Management product area, contribute to architectural decisions, mentor engineers, and ensure high engineering standards across teams.

Design, build, and maintain scalable AI/ML pipelines for data processing, model training, and deployment. Collaborate with data scientists and engineers to implement and optimize AI solutions, troubleshoot pipeline issues, document best practices, and develop MVP code to transition into production-ready systems.

Own end-to-end month‑end close (5-day target), maintain GL and reconciliations, run AP and vendor relationships, automate accounting workflows using AI/LLMs and Python, ensure audit-ready results, support audits and FP&A, and build integrations against NetSuite and financial systems to compress the close.

As a Growth Engineer, you will integrate Ritual's AI infrastructure with partner applications, supporting integration lifecycle and developing documentation for APIs and SDKs.

As a Fullstack Software Engineer, you will develop products for the post-purchase experience by implementing features, maintaining code quality, and mentoring other engineers.