Top Tech Jobs & Startup Jobs in Toronto

Design, develop, and deploy large-scale recommender systems and ML models (including LLMs) for personalized retrieval and ranking. Build and operate big data pipelines, production MLOps, and cloud-based infrastructure to serve real-time recommendations and drive marketplace and advertising revenue.

Design, deploy, and operate enterprise SSO and IAM solutions across corporate and partner applications. Lead federation architecture (SAML/OIDC/OAuth/WS-Fed), integrate apps and APIs, analyze logs and tokens, troubleshoot complex authentication/network issues, enforce Zero Trust and contextual MFA, automate workflows with scripting, and participate in on-call rotations for production support.

Lead analytics strategy for C2C M&A integrations, driving product analytics, experimentation, metric standards, AI-enabled prototypes, and cross-functional data solutions to improve seller outcomes and business performance.

eBay is hiring ML Scientists and ML Engineers to design advanced models for ranking, recommendations, personalization, and pricing, and to productionize those models. Responsibilities include feature engineering with Zipline, building ETL/ELT and inference pipelines, MLOps, model serving, monitoring, deployment automation, and cost/performance optimization.

Lead and develop a team of data engineers building scalable real-time and batch pipelines and cloud data platforms. Set technical direction, manage major initiatives, and establish practices for architecture, testing, observability, reliability, and operational excellence. Partner with Product, Data Science, Analytics, and Engineering teams to deliver trusted data solutions supporting analytics, experimentation, machine learning, personalization, and high-volume marketplace experiences.

Design, build, and operate scalable real-time and batch data pipelines using Kafka, Spark, Flink, Airflow, Databricks, AWS, and dbt. Implement data quality frameworks, optimize distributed workloads, and develop reliable cloud-native data platforms. Own initiatives from architecture through production support while collaborating with Data Science, Product, Analytics, and Engineering teams. Create reusable engineering patterns, improve system scalability and performance, and maintain documentation for critical data systems.

Design, develop, and own scalable real-time and batch data pipelines using Kafka, Spark, Flink, Airflow, Databricks, and AWS. Implement data quality frameworks, oversee projects from design through long-term support, identify scalability risks, document systems, and collaborate with data science, product, and engineering teams to guide technical roadmaps.

Lead architecture and implementation for marketplace platform integrations. Design scalable distributed services, write production backend code in Java, conduct design and code reviews, and translate ambiguous business goals into technical solutions. Collaborate with engineering teams across platforms, stacks, and geographies while shaping integration patterns, maintainability, and long-term scalability.

Design and deliver end-to-end product experiences for buyers and sellers, from discovery through high-fidelity prototypes. Collaborate with product and engineering partners, use research and data to inform decisions, and create journey maps, wireframes, and prototypes that meet business and user goals.

Lead monetization strategy for key categories by designing fee structures, pricing models, promotions, and experiments. Partner with product, engineering, analytics and global stakeholders to analyze elasticity, deliver data-driven recommendations, validate price changes, and support execution to drive growth and long-term value for buyers and sellers.