Top Python Jobs in Toronto

Lead development of back-end systems and end-to-end data/ML pipelines, build and deploy generative AI workflows, design and consume performant APIs, contribute to AI/ML architecture, mentor engineers, and communicate progress to leadership.

Develop and maintain backend services and data pipelines to support AI/ML and GenAI workflows. Build and consume secure, scalable APIs, work with microservices on Kubernetes, collaborate on design and code review, and grow applied ML skills under senior mentorship.

Design, standardize, and implement PLC/SCADA and IIoT-based automated test systems for intelligent pumps. Lead smart testing strategy, firmware validation, data acquisition/analytics, dashboards, and global standardization. Integrate test systems with MES/ERP/PLM, support audits, and drive continuous improvement and digital transformation across manufacturing operations.

Design and develop mechanical products: create CAD models, assemblies, and production drawings; perform calculations, simulations, GD&T, and tolerance stack-ups; contribute to DFMEA; maintain BOMs in PLM; collaborate with manufacturing, quality, suppliers, and sales to ensure manufacturability and certification.

Drive strategy and execution for simulation and neural reconstruction products: conduct customer discovery, define roadmaps, translate technical AI and simulation needs into scalable features, track success metrics, collaborate with engineering and GTM, and support launches. Role includes frequent customer interaction and on-site visits.

Build, train, evaluate, and deploy production computer vision models (detection, segmentation, OCR, barcode decoding, visual search). Own dataset quality, tooling, model releases, inference exports, and monitoring. Collaborate cross-functionally to improve model performance, robustness, and deployment for retail robotics and edge environments.

Lead design, integration, and optimization of production robot perception pipelines (detection, segmentation, depth, tracking, SLAM). Bridge computer vision and robot autonomy, optimize real-time inference on edge GPUs, debug field failures, define system benchmarks, and provide technical leadership and mentorship across teams.

Own and improve annotation systems, workflows, and tooling to produce high-quality training data. Build Python and web tools, integrate model-assisted labeling and active learning, implement data quality checks, support dataset versioning and evaluation, and coordinate cross-team efforts to measure and improve annotation throughput and model impact.

Lead administration and support of corporate Microsoft infrastructure, VDI/RDS access platforms, virtualization, storage, backups, and cloud services. Perform AD domain/forest migrations, replace legacy VDI and load‑balancing stacks, maintain documentation, resolve incidents to SLA, participate in projects and on‑call rotation, and collaborate with NOC, InfoSec, DevOps, and L2 teams.

Lead full‑stack development of an AI‑driven web application, designing architecture and end‑to‑end AI/ML systems. Build features across front end and back end, ensure security, scalability, and observability, prototype ML innovations, mentor engineers, and partner with product, design, and business teams to drive technical decisions and delivery.

Optimize end-to-end GPU performance for real-time autonomous driving workloads: develop and optimize parallel GPU algorithms and inference pipelines, profile and eliminate bottlenecks across computation and memory, debug GPU software for latency/throughput improvements, and collaborate on onboard GPU software architectures for embedded platforms.

Deliver end-to-end voice AI solutions for enterprise customers: prototype to production, build full-stack integrations (Python, JavaScript/TypeScript) with CRMs/ERPs, partner with sales, scope and resolve blockers, codify reusable patterns, translate field feedback to product recommendations. Fluent Mandarin required to support China-based customers; occasional international travel may be needed.

Senior hands-on full-stack engineer who leads architecture, drives cross-team technical roadmaps, implements scalable Django/React systems, improves CI/CD and testing practices, mentors engineers, and partners with product, clinical, and executive stakeholders to translate business needs into durable technical solutions.

Develop and maintain infrastructure platforms for AI services, build APIs, manage Kubernetes clusters, and automate workflows using CI/CD practices.

The Technical Architect develops scalable platforms and systems, collaborates with product teams, and leads architecture across data solutions and integrations, ensuring best practices and mentoring developers.

The Associate AI Engineer will assist in building AI-powered backend services, integrating APIs, and developing data pipelines while collaborating with experienced engineers and teams.

The Senior Product Manager will lead the development of AI-driven solutions to optimize MLR processes and improve compliance for life sciences companies.

Operate and automate cloud-native infrastructure across environments; maintain core platform services; troubleshoot and optimize workloads; implement IaC and configuration management; build automation to improve reliability; support CI/CD, observability, incident response, security, and compliance practices.

Lead and grow a Data Engineering team to build production data pipelines, medallion datasets, and reusable data products. Drive architecture, engineering standards, design reviews, and cross-functional delivery. Partner with Product, Analytics, Data Science, and Platform to enable governed, reliable data foundations for analytics and AI. Mentor engineers and manage multiple concurrent initiatives to deliver predictable outcomes.

Lead design and implementation of foundational platform components (authentication, API gateways, interservice communication, caching, shared libraries). Mentor engineers, drive cross-team alignment on architecture, own features end-to-end, improve developer experience, and ensure high availability, performance, and security while shipping frequently and modernizing core systems.

Lead design and delivery of microservices-based applications using Agile and DevOps. Build CI/CD pipelines, observability, and security practices; mentor DevOps teams; troubleshoot production issues and deliver enterprise solutions.

Lead design and production of next-generation search and personalization systems using LLMs, dense vector retrieval, GNNs, multi-stage ranking, and reinforcement learning. Drive GPU-based deployment (e.g., Triton), ensure <100ms latency, mentor applied scientists and MLEs, and partner cross-functionally to productionize scalable, reliable search and recommendation experiences.

Design, build, and maintain scalable data infrastructure and ETL pipelines using Python, SQL, PySpark, and Microsoft Fabric. Collaborate with Analytics and Data Science to translate requirements, optimize queries, investigate and resolve data issues, and support reliable pipeline operations and system architecture.

The Senior Systems Developer will automate processes, build integrations, manage infrastructure utilizing modern tools, and mentor junior team members while enhancing automation strategy.

Drive architecture and implementation of an internal AI/agent platform: design agent runtimes and SDKs, define eval-driven release gates, safety, telemetry, and AuthX, partner with product teams to integrate reusable capabilities, set standards for prompt management and observability, write and ship production code, and mentor engineers.