Top AI Jobs in Toronto

Founding technical role to design, build, and deploy internal AI tools and agents using LLMs and retrieval systems. Partner with investors and the data team to accelerate sourcing, diligence, portfolio insights, and define CRV's AI strategy through rapid prototyping and production-grade systems.

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 end-to-end delivery of AI deployments for financial services clients: define features, translate business needs into technical specs, run agile sprints, drive adoption and change management, ensure measurable program outcomes, and expand commercial relationships while collaborating with engineers, product, design, and investment teams.

The role involves enhancing a graph compiler for ML models, optimizing performance across hardware platforms, and collaborating on core technologies.

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

The role involves rapid prototyping and architecting production LLM pipelines for AI in marketing workflows. Responsibilities include developing proofs of concept, making AI architecture decisions, building production data agents, and understanding user workflows for seamless AI experiences.

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.

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.

Build and operate high-throughput experimentation and recommendation infrastructure. Design APIs and services, use agentic AI workflows (LLMs) for development, ensure performance and reliability, participate in on-call, mentor teammates, and codify AI-native engineering practices.

The role involves managing large-scale AI infrastructure projects, focusing on deployments, risk management, and cross-functional coordination while ensuring alignment with business objectives.

The engineer supports simple data hall designs, drafts AutoCAD drawings, assists with capacity planning, and learns data center principles under supervision.

Lead large-scale AI infrastructure deployment programs, manage project execution for GPU clusters and data center infrastructure, and mentor junior project managers.

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.

Drive the expansion of software development and AI services by managing client relationships, building sales pipelines, and negotiating contracts.

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.

Design and build AI-driven interactive prototypes and production-ready flows using AI coding tools. Own prompt-to-pipeline solutions, validate via experiments and user research, produce high-fidelity UX in Figma, and collaborate with engineering to move prototypes to production while aligning business, design, and tech.

Lead the design and delivery of Agentic AI solutions to enhance customer experience and operational efficiency, focusing on enterprise-wide AI transformation.

Lead AI feature design and delivery, build large-scale ML systems, mentor engineers, and define best practices across the engineering organization.

Lead live sessions, office hours, and project reviews for senior engineers transitioning into system architecture. Provide detailed architecture critiques, mentor students one-on-one, run architecture review boards, record instructional videos, conduct mock interviews, and coordinate supporting instructors to ensure high technical standards and student readiness for architecture roles.

Author and refine a systems-engineering curriculum for experienced engineers: shape syllabus, define learning objectives, produce and fact-check AI-assisted lessons, design hands-on projects, write rubrics and reviewer guides, and iterate with an LX designer. Part-time (15-20 hrs/week) for ~4-6 months.

Build and ship LLM- and agent-powered product experiences for North, designing interfaces, evals, observability, and feedback loops to improve reliability and user outcomes. Collaborate with modelling, product, design, and customers to turn failures and feedback into measurable product and model improvements.

Design, build, and operate CI/CD, Kubernetes-based platforms, deployment automation, and observability for engineering workflows. Improve reliability, performance, and scalability across cloud and on-prem environments, debug cross-boundary failures, perform root-cause analysis, and deliver durable platform software and self-service tooling.

Execute hardware bring-up, validation, and telemetry monitoring for Cerebras AI clusters in data centers. Perform power-on sequencing, first-line troubleshooting, log collection, incident support under senior guidance, and contribute feedback to tooling and documentation while learning system architecture and networking fundamentals.