Top AI Jobs in Ottawa

S32 seeks Applied AI Research Scientists to explore new approaches, algorithms, and methodologies to advance AI systems across portfolio companies. Candidates will drive research, shape company direction, and collaborate with founders to apply research outcomes to product and business needs.

Seeking Applied AI Research Scientists to develop and explore new AI approaches, algorithms, and methodologies to drive AI systems across S32 portfolio companies and shape company direction.

Design and build applications in Python, collaborate with clients, optimize performance, and ensure code quality in AI-driven projects.

Design and lead end-to-end AI/ML and GenAI architectures (data pipelines, training, inference, MLOps). Advise clients, integrate LLMs, build RAG systems, benchmark platforms, mentor teams, ensure responsible AI, and align ML strategy with business goals.

The AI Data Expert will review and evaluate AI-generated outputs and textual content, ensuring cultural relevance and quality. Responsibilities include content analysis, assessing multimedia materials, and providing structured annotations while adhering to detailed guidelines. Native fluency in French and strong English skills are essential, with previous experience in AI evaluation preferred.

Evaluate and review AI outputs, generate or assess content, and ensure cultural relevance and accuracy in various media for AI projects.

The Applied AI Engineer will develop AI-powered systems to streamline internal processes, collaborating with various departments to enhance efficiency and automation. This role involves problem ownership, system design, and deploying solutions that leverage AI technology while ensuring user adoption and long-term value.

Design and implement AI-driven tools to improve workflows across teams. Collaborate to identify internal problems AI can solve, and prototype solutions quickly.

Lead enterprise AI strategy and roadmap; build and scale cross-functional AI/ML teams; architect and deliver LLM, RAG, predictive and data-heavy AI products; establish MLOps, governance, cloud-native platforms (Azure/Databricks/AWS/GCP); drive product lifecycle, KPI tracking, security, and responsible AI practices.

Four-month full-time research fellowship supporting empirical AI safety projects using external models and APIs. Fellows receive mentorship, compute funding, and workspace access to produce public outputs (e.g., papers) across safety, robustness, interpretability, RL, and societal-impact topics.

Lead design and delivery of AI solutions (RAG and agentic architectures) for asset and wealth management clients. Architect retrieval pipelines, semantic models, GraphRAG, and cloud integrations. Manage project planning, governance, budgets, technical handover, and mentor development teams while promoting best practices and responsible AI.

Design, deploy, and operate Kubernetes, GPU, and HPC compute across bare metal and cloud. Manage scheduling (Slurm/K8s), CUDA and drivers, storage, observability, IaC, deployment workflows, and support researchers to ensure reliable, scalable inference and research infrastructure.

Lead end-to-end operations for an AI-native Physicist Fellowship: recruit fellows, run selection processes, coordinate advisors and technical teams, design cohort programming, track metrics, and build ecosystem relationships to support AI-driven scientific research.

Senior technical leader responsible for architecting production-grade AI infrastructure for media & entertainment partners. Translate business needs into scalable GPU, storage, networking and inference solutions; validate ISV integrations; influence product roadmap; engage CTO-level stakeholders; and grow a team as the vertical scales.

The role involves architecting AI solutions for compliance, ensuring regulatory adherence, automating processes, and enhancing team capabilities through technology and training.

The role involves designing, building, and deploying machine learning models, collaborating with teams to address business problems, and mentoring other data scientists.

Lead design and implementation of LLM-powered product features, integrate AI into Vanta systems, instrument evaluations and monitoring, collaborate with platform and product teams, make pragmatic technical tradeoffs, mentor engineers, and drive AI product quality and adoption to help customers accelerate compliance and risk management.

The Principal Engineer will architect and own the Shop Builder platform, defining APIs, developing tools for developers and AI agents, and ensuring the platform's technical standards and documentation are met.

Lead a team to deliver tools and API solutions for the Shop Builder platform. Coordinate cross-team dependencies and maintain engineering standards while actively contributing code and driving technical decisions.

Lead end-to-end RFP lifecycle and implement an AI-augmented proposal workflow. Build and maintain an answer corpus, operate and tune RAG/retrieval pipelines, coordinate SME review, and produce persuasive, compliant proposals. Track win rates and continuously improve systems to reduce SME review time and increase competitive win rates.

Lead hardware-software co-design to enable AI/HPC and agentic AI stacks on RISC-V CPUs. Integrate and optimize low-level kernel infrastructure, runtimes, distributed execution, memory systems, and developer tools, collaborating with architects, compiler engineers, and kernel developers to meet performance targets.

The role involves creating narrative-driven video content using AI tools, managing end-to-end production workflows, and ensuring visual coherence across projects.

Manage multilingual data collection and Large Language Model evaluation projects, ensuring quality assurance and effective global team coordination.

The Senior Applied AI Engineer will build AI-driven interactive product demos, collaborating with design and engineering teams to create intelligent multimodal experiences.

The role involves designing scalable AI solutions, managing large-scale AI deployments, building client relationships, and delivering presentations. Requires experience in MLOps and knowledge of ML ecosystems.