Top Tech Jobs & Startup Jobs in Toronto

Lead the Content Foundations engineering team and evolve Scribd’s high-scale document ingestion platform into a real-time, AI-native system. Responsibilities include setting technical strategy, integrating AI and ML capabilities, overseeing distributed data infrastructure, ensuring security and operational reliability, managing the roadmap, hiring and developing backend and AI data engineers, and partnering with product and engineering leaders across the organization.

Leads performance and organic growth strategy across paid search, paid social, affiliate, SEO, and LLM-driven discovery for three brands. Manages channel experts, budgets, attribution, reporting, experimentation, and marketing technology to optimize acquisition efficiency and ROI. Partners with brand and creative teams on integrated campaigns, develops emerging channels, and applies data, AI tools, and unit economics to drive profitable growth.

Own the acquisition product roadmap and engineering priorities to drive durable user growth. Define target audiences and channel mix, build product-driven acquisition mechanics (referrals, growth loops), enable channel effectiveness (discoverability, search/AI readiness, integrations, tracking), test new acquisition tactics, and align product investment with Performance Marketing, SEO, Partnerships, and Brand while measuring long-term subscriber value.

Lead the recommendations product across candidate generation, ranking, and presentation for Scribd. Define multi-year strategy and metrics, translate retrieval and ranking research into production, run experiments to improve engagement and conversion, partner with ML, engineering, design, and analytics, and communicate roadmap and impact to stakeholders.

Leads Scribd’s content intelligence and UGC supply portfolio, owning corpus classification, metadata, quality, gap analysis, AI infrastructure, contributor experiences, and content acquisition strategy. Partners with ML, engineering, data science, consumer product, and business development teams to connect content supply with business value. Manages senior product leaders and established engineering and analytics programs while setting portfolio roadmaps and representing content strategy with executives.

Design, build, and operate Rust services powering Scribd’s large-scale Content Library and core infrastructure. Own features end to end, evolve Python tooling, optimize DataFusion, Parquet, S3, caching, and PostgreSQL/Aurora systems, and strengthen governance through lineage, authorization, and deletion controls. Lead cross-functional technical projects, support platform users, mentor engineers, improve developer workflows, and maintain production reliability through observability, on-call, and incident response.

Own and set technical direction for the Everand backend, building scalable, reliable systems for discoverability, personalization, and core consumption journeys. Drive architecture, platform health (CI/CD, staging, DBs, queues, cost, observability), mentor engineers, lead cross-team planning, modernize legacy systems, and partner with product, design, analytics, web/mobile, and ML to support experimentation and telemetry-driven decisions.

Design, develop, and deploy machine learning and NLP solutions at scale. Work with cross-functional teams to build content classification, representation learning, search, and recommendation models using classical ML, deep learning, and LLMs. Process large datasets with Python, SQL, and Spark, and communicate results to stakeholders with clear documentation.

Lead technical direction and architecture for the Fable backend, own platform reliability (databases, CI/CD, queues, observability), run incident response and postmortems, mentor engineers, collaborate cross-functionally with product/design/ML, and build platform capabilities enabling faster, safer delivery.

Lead and scale paid social advertising across Meta, TikTok, Reddit, and emerging platforms to drive user acquisition for subscription products. Own budgets, audience targeting, structured testing, creative collaboration, AI-accelerated experimentation, analytics, attribution and incrementality work, and conversion rate optimization across landing pages. Communicate results and build reusable playbooks for the performance marketing team.