Top Research Jobs in Ottawa

The role involves designing scalable data pipelines for 3D, video, and sensor data, optimizing infrastructure, and productionizing ML models with researchers.

The research engineer will focus on solving the structure from motion problem, contributing to 3D reconstruction in various industries using AI.

Research and build efficient ML systems for large-scale LLMs and agentic RL: design algorithms and system techniques, prototype in training/inference stacks, run large-scale experiments, and translate findings into production or publications.

Execute synthesis, place-and-route and STA for ASIC partitions from RTL to silicon. Collaborate with architects, RTL designers and DFT engineers to close EM/IR, LEC and physical verification signoff. Improve physical design methodologies (synthesis, PnR, EMIR, PDN), troubleshoot flows and work with EDA vendors to resolve issues while meeting tight schedules and low-power goals.

Lead design and execution of a 3–5 year fundraising strategy; personally cultivate and close five- and six-figure major gifts; manage donor CRM, reporting, dashboards, and fundraising collateral; partner with CEO and Board for donor engagement; align projects to donor goals; mentor a small fundraising team; track performance against KPIs; travel for donor meetings and events.

Design, train, evaluate, and optimize agent-native LLMs and RAG pipelines for enterprise use. Build training and RL pipelines (RLHF/DPO/PPO), embedding-based memory, evaluation harnesses, observability, and inference optimization across cloud and on-prem environments.

Participants are needed for an AI technology research study, offering compensation up to $600 for ~1.5-2 hours of participation over one week, requiring skills in tech-related roles.

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.

The Research Scientist will develop and enhance simulation agents using advanced machine learning techniques, mentor junior team members, and publish research findings.

As a Research Intern, you will prototype and productionize research in AI and cryptographic schemes, collaborating with teams for real-world impact.

As a Research Intern at N1, contribute to market/product or technical research in blockchain, developing analytical skills.

The Senior Research Consultant will advise clients on market research, design studies, interpret results, and integrate AI into research processes.

Support and maintain GxP-compliant quality systems: plan and conduct internal audits, manage CAPAs and deviations, review NCs and quality indicators, support vendor qualification and RFIs, assist with inspection readiness and client audits, create training and quality documentation, and perform IP release with GMP background.

Partner with portfolio and risk managers to develop quantitative risk models, analyze U.S. power markets, improve backtesting and simulation infrastructure, attribute performance, track P&L and exposures, and deliver actionable insights to scale the trading and risk platform.

Work directly with physicists to drive adoption of an AI research platform: own user lifecycle from discovery to retention, design onboarding and scalable workflows, build guides and tooling, identify UX friction, and act as a technical point of contact while partnering with research and engineering.

The Senior CRA ensures quality site management and monitoring of clinical trials, addressing protocol-related issues while maintaining compliance and investigator relations.

The role involves designing and implementing machine learning systems for knowledge representation and temporal reasoning, focusing on organizational intelligence. Responsibilities include building LLM-powered pipelines, developing memory algorithms, and researching various ML techniques.

Build and scale core research infrastructure and agentic systems across backend, frontend, and model integrations. Own reliability, observability, and performance; ship research-proven features to production rapidly and develop shared tools and SDKs to accelerate Research, QA, and Engineering.