Top Python Jobs in Toronto

Partner with Marketing as the embedded data science lead to build marketing measurement, attribution, LTV/ROAS/CAC models, run experiments, analyze the full funnel, create forecasts and dashboards, and influence channel strategy and budget allocation.

The Senior ML/RL Engineer will develop behavior models, implement RL algorithms focusing on safety, design reward functions and optimize training environments while collaborating across teams.

As a Staff Software Engineer at Juniper Square, you'll lead architectural decisions and develop AI-powered systems, mentoring engineers and ensuring high-quality technical standards while collaborating with cross-functional teams.

Develop and deliver user-friendly software for B2B SaaS products. Collaborate with teams on both front-end and back-end development.

As a Senior Software Engineer, you will design and deliver user-friendly software, manage APIs, and create scalable microservice architectures.

The Machine Learning Engineer will develop and deploy ML models, leveraging analytical skills to automate processes and reveal data value.

The role involves end-to-end machine learning lifecycle management, including data processing, model development, rigorous testing, and production deployment, focusing on large quantitative models for AI-first products.

The Machine Learning Engineer will manage the ML lifecycle, develop models, ensure performance, and collaborate with a diverse team to build AI-first products.

As a Data Scientist at Sardine, you'll design and deploy data-driven solutions to prevent fraud, collaborating with clients and engineering teams to build and optimize machine learning models.

Serve as a trusted technical advisor designing and implementing Coveo AI relevance solutions. Lead architecture, requirements, and delivery across customer ecosystems, collaborate with stakeholders, enforce best practices and governance, and support agile delivery and product feedback.

The Manufacturing Bring-up Engineer oversees system testing and validation, collaborating with cross-functional teams to automate workflows and enhance manufacturing efficiencies.

Responsible for software integration and quality for Cerebras AI platform, focusing on automation, debugging, and cross-team collaboration. Develops QA strategies and testing methodologies to ensure product quality.

Design, build, and optimize cloud-native lakehouse data pipelines and curated data products using Python and SQL. Own data modeling, performance tuning, observability, governance, and reusable platform patterns to support analytics, embedded reporting, operational workflows, and AI/ML datasets. Mentor engineers, lead reviews, and improve platform reliability, cost efficiency, and data quality.

Build and deploy generative ML features for Ideogram's app and API: fine-tune and ship models, design evaluations and datasets, run error analyses, monitor reliability, and collaborate with research, infra, product, and clients to meet quality, latency, and cost goals.

Lead and build shared AI infrastructure and production-grade agents for a product analytics team. Establish repo standards, evaluation tooling, governance compliance, monitor production agents, close data pipeline gaps, and drive adoption across ~35 analysts and 60+ products while interfacing with cross-team AI and data platform partners.

Design, train, and deploy real-time computer vision and multimodal perception models for person detection, tracking, pose/gesture/emotion recognition, and scene understanding. Build data collection/labeling pipelines, optimize models for edge inference, integrate perception with behavior and firmware, debug failures, and evolve perception architecture from prototype to deployed robot systems.

Design Verification Engineer responsible for verifying Tensix IP, building reusable SystemVerilog/Python testbenches and DV infrastructure, developing constrained-random and directed tests, closing coverage, debugging RTL/testbench/workload issues, and integrating CI/CD, simulation/emulation, and containerized regression systems. Collaborates with design, firmware, compiler, and architecture teams.

Provide L2 production support for data and client platforms in a 24x6 global follow-the-sun model: incident triage, escalation, SLA-driven communications, problem management, monitoring/automation (Grafana, ITRS Geneos), scripting-based automation (Shell/Python), SQL-based data investigations, change management, and mentoring SMEs while contributing to cloud migration and AI-assisted operations initiatives.

Lead and execute perception R&D and engineering for factory robots: define multi-year roadmap, architect perception pipelines (detection, segmentation, 6-DoF pose, scene understanding), drive sensor fusion and calibration, establish data/model workflows and deployment practices, integrate with planning/control, hire and mentor engineers, and evaluate research for production adoption.

Design, build, deploy, and operate an internal AI platform and AI-powered developer workflows. Implement CI/CD for models, prompts, and evaluations; integrate Bedrock/agent frameworks; ensure security, observability, reliability, and cost/version controls; respond to incidents and participate in on-call rotations; promote AI best practices and lead architecture discussions.

Design, build, and maintain integrations and automations between internal systems and third-party platforms (ERP/finance). Collaborate with stakeholders, use iPaaS tools and API standards, perform code reviews, participate in on-call rotation, and deliver well-tested integration projects on schedule.

As a Software Engineer in Data Infrastructure, you will build and maintain high-performance data storage systems for AI training, collaborate with experts, and optimize data processing.

Build scalable ML data pipelines for Waabi's autonomous driving platform. Design, optimize, and manage datasets and training processes while collaborating with scientists and engineers.

Contribute to the development of Waabi World, improve simulation scalability, and design orchestration software for autonomous vehicle simulations.

The Principal Platform Engineer will design and implement AI platforms, including distributed systems and orchestration frameworks, mentor engineers, and define best practices for LLM integration.