Top AI Jobs in Ottawa

Lead architecture and performance exploration for next-generation AI inference accelerators. Build analytical models and simulation frameworks, define subsystem interfaces and roadmaps, and drive hardware/software co-design with compiler, runtime, ML, and silicon teams to optimize latency, throughput, memory, interconnects, power, and cost for evolving LLMs and transformer-based workloads.

Lead product vision, roadmap, and delivery for AI and analytics across the Intelex platform. Conduct customer discovery, define PRDs and success metrics, partner with engineering and design, manage end-to-end launches, instrument and monitor feature adoption and quality, enable go-to-market teams, and ensure AI governance, explainability, and compliance for enterprise EHSQ use cases.

The Senior AI Compute Infrastructure Engineer will manage and optimize GPU and accelerator clusters for AI workloads, collaborate with teams, and ensure reliable performance and cost efficiency.

Embed with enterprise customers to design, build, and deploy production agentic AI workflows. Integrate platform with customer systems, handle security and compliance reviews, drive adoption and expansion, and feed product improvements based on field signal.

Embed with enterprise customers to deploy production agentic AI workflows: integrate data sources, identity, CRMs and APIs; handle security, SSO/SCIM, isolated VMs and compliance; drive adoption, instrument usage, and feed product improvements to scale deployments.

Embed with client operators, learn and rebuild critical business processes, and deliver production GenAI/LLM systems on AWS. Own design, shipping, evaluation, and operational handoff while working cross-functionally with senior stakeholders to move business metrics.

Design, build, and productionize LLM-powered systems (adaptive content, tutors, evaluators) and AI pipelines (RAG, embeddings, fine-tuning). Prototype and optimize models across modalities, define AI safety/evaluation/observability practices, and collaborate with product and engineering to measure learner outcomes and iterate.

As a Staff Software Engineer, you'll design and deliver a core data platform, focusing on architecture, pipeline components, and AI integration. This hands-on role emphasizes creating production code and establishing technical standards within a small team.

Sell AI-powered solutions to automotive dealerships in the Maritimes. Own the full sales cycle—prospecting, discovery, demo, negotiation, and close—build relationships with dealer leadership, present ROI-focused demos and proposals, maintain pipeline, forecast accurately, and consistently meet revenue targets.

Own and automate the end-to-end ML lifecycle: build, deploy, monitor, test, and retire models at scale. Design production-grade, highly available ML infrastructure and CI/CD pipelines, implement governance, and collaborate with engineering and security teams.

Design and run automation-driven, AI-agent-assisted attack campaigns and red-team simulations against Wealthsimple products and infrastructure; build and improve automated testing pipelines, AI agents, and tooling; triage AI-generated findings into high-signal vulnerabilities; collaborate with platform engineers and AppSec to integrate adversarial testing into the SDLC and support remediation.

Build, operate, and scale cloud-native backend services and APIs for a high-volume vehicle marketplace. Embed AI-driven capabilities into features, use AI tools to accelerate development, participate in on-call rotations, improve reliability, and collaborate with Product, Data, Infrastructure, and SRE teams to deliver production-ready systems.

Own and evolve Directive's web surfaces for Stratos and company sites: build campaign and reporting UIs, integrate ad/CRM APIs, manage background jobs, containers, CI/CD, databases, telemetry, auth, and LLM integrations; stabilize inherited code and ship production features iteratively.

The role involves designing and integrating intelligent translation workflows using machine translation, generative AI, and prompt engineering, ensuring compliance and performance optimization.

Own full sales and partnership cycle to bring voice AI to mobile service robots: engage senior robotics decision-makers, qualify and prioritize opportunities, close deals, and shape the commercial playbook while operating autonomously within a small technical team.

Lead technical engagements with robotics customers to design and integrate voice AI into mobile robots, own POCs and technical evaluations, clear deployment roadblocks, collaborate with sales/product/services, and feed customer learnings into the product. Travel across Europe for onsite evaluations (20–30%).

Join a VC-backed startup network connecting Director/VP-level AI/ML leaders to portfolio companies. Lead AI strategy, build and scale ML teams, deploy and improve production ML systems, set model quality and responsible AI standards, partner with product and engineering, oversee data and MLOps, evaluate models and tooling, and communicate strategy to executives and boards.

Join a talent network connecting senior/staff applied AI scientists to VC-backed startups. Responsibilities include researching and developing ML methods, fine-tuning foundation models, designing experiments and evaluation frameworks, building prototypes, collaborating with engineering/product to productionize models, improving model robustness and efficiency, curating datasets, investigating failures, mentoring peers, and communicating results to stakeholders.

Join a talent network connecting Principal AI/ML Engineers with VC-backed startups. Responsibilities include architecting and deploying production ML/DL models, researching state-of-the-art methods (LLMs, transformers, RL), building scalable training/inference pipelines, implementing robust MLOps, optimizing model performance, and leading technical strategy and teams.

Join a talent network connecting founding AI engineers with VC-backed startups. Responsibilities include designing, building, and deploying ML/DL models, creating scalable data pipelines, optimizing real-time and batch model deployments, developing RAG and LLM systems, and aligning AI strategy with founders and product goals.

The Data Scientist will develop data labeling strategies, optimize datasets for LLMs, analyze data quality, and collaborate with engineering on data processing pipelines.

Design, build, deploy, and support scalable backend APIs and agentic AI solutions using Go. Architect microservices and cloud infrastructure (Azure/GCP), integrate data platforms, create API docs and partner enablement assets, and ensure operational readiness with CI/CD, SLOs, and security-by-design.

Design, develop, fine-tune, and optimize generative deep learning models (GANs, VAEs, transformers). Collaborate with cross-functional teams to integrate and deploy AI solutions, troubleshoot model issues, document models, and communicate technical concepts to non-technical stakeholders.

Lead product marketing for Procore AI & Data products: own positioning, messaging, launches, competitive positioning, sales enablement, and cross-functional GTM programs. Collaborate with Product, Demand Gen, Sales, and global Marketing to create customer-facing content and drive adoption.

Provide legal guidance on privacy and AI governance across product, engineering, and commercial teams. Draft and negotiate DPAs/BAAs and AI terms, lead PbD/PIAs/DPIAs/AI risk assessments, maintain governance policies and RoPAs, manage DSARs and cookie compliance, respond to customer privacy/AI inquiries, monitor global privacy and AI regulation, and interface with regulators and works councils.