Top Machine Learning Jobs in Ottawa

Design, build, and operate scalable backend services in Python or Go to power underwriting decisioning. Integrate statistical and ML models, implement APIs (REST, gRPC/GraphQL), ensure observability and testing, lead projects, and collaborate with product, data science, and underwriting teams to automate underwriting workflows.

The role involves analyzing biological mass spectrometry data, developing software tools, and scaling workflows for AI and human consumption in drug safety assessment.

Manage requests for new ServiceNow reports and dashboards, resolve dashboard/reporting incidents, train users on dashboards, build executive KPIs and scorecards, engage stakeholders to gather requirements, and apply AI/Generative AI for reporting automation and insights.

Develop and optimize auto-labelling systems using ML and computer vision, manage data pipelines, and collaborate with researchers.

The Forward Deployment Engineer will deploy and optimize Generative AI solutions, architect scalable infrastructure, and implement data pipelines across multi-cloud environments while collaborating with cross-functional teams to maximize business value.

The VP of Data & AI Engineering leads Duck Creek's enterprise data and AI strategy, overseeing global teams, implementing scalable platforms, and ensuring data governance and responsible AI practices.

The Director of Engineering will lead and scale Buzz Solutions' engineering organization, focusing on AI, infrastructure, and platform systems while ensuring best practices and high-quality solutions.

The Senior Account Executive will develop relationships with utility clients, lead sales initiatives, negotiate contracts, and maintain sales activities in Hubspot to achieve sales targets.

Lead product management for AI tools in software/SaaS, manage product lifecycle, drive strategic roadmap, and ensure product adoption through iterative shipping and user feedback.

Bay Area-based hunter Enterprise Account Executive responsible for prospecting, developing, and closing new enterprise business for Anyscale. Manage complex sales cycles, achieve quotas, lead CxO engagements, qualify opportunities, collaborate with marketing, and drive ongoing account growth while advising customers on ML, compute, and cloud solutions.

Define and build Wave's internal risk and payments operations platform. Own strategy and roadmap for tools used by Risk, Fraud, Compliance, Support, Finance, and Payments Operations. Replace manual workflows with scalable decisioning, case management, and automation. Partner cross-functionally with Engineering, Data, and business teams to improve efficiency, controls, and customer outcomes.

Own commercial strategy and operations for enterprise pharma and AI accounts: drive pilots-to-revenue, account expansion, pipeline management, pricing, forecasting, and deal strategy. Build cross-functional relationships, push deals through legal/procurement/IT, act as CEO counterpart to shape strategy and product roadmap, and be highly present in person with customers and at conferences.

The Applied Scientist will transform raw data into actionable insights by developing machine learning models for personalization, ranking, and optimization to enhance conversion and revenue. This role emphasizes building production systems, frameworks for experimentation, and communication with team members regarding technical challenges.

Embed with clients to gather requirements and design AI-driven solutions for fraud and fincrime. Architect, train, evaluate, and deploy custom AI agents and workflows, optimize model performance, establish risk metrics and evaluation pipelines, and collaborate with engineering/product teams to scale into production.

Lead the product vision for innovative AI technologies, translating research into marketable products, and collaborating with cross-functional teams.

Seeking a Research Scientist to develop AI models for enhancing 3D reconstruction processes, requiring strong skills in computer vision and neural reconstructions.

The Junior Data Scientist will design and develop data models using Machine Learning and Analytics for trading and compliance in finance.

Lead the data and ML product vision: define roadmap, prototype models on noisy behavioral datasets, translate signals into user-facing features, partner with engineering to productionize ML, and generate insights to inform product roadmaps.

Lead Vegetation Intelligence product, owning roadmap from ML detection models to customer-facing risk products. Advance detection models, integrate outputs into outage and ignition risk, run user research, and translate model capability into actionable B2B products used in the field.

Lead end-to-end technical programs for ML infrastructure (inference, serving, efficiency, endpoints). Coordinate cross-functional teams, prioritize overlapping projects, manage timelines, budgets and scope, drive incident management and continuous improvement, and communicate status to engineering and leadership.

Build and deploy production AI/ML features for cybersecurity: design autonomous agent architectures and multi-agent workflows, select and optimize LLMs/SLMs, manage end-to-end ML pipelines, optimize inference and MLOps infrastructure, apply deep learning, time-series and GNN techniques for threat detection, and create automated benchmarking tied to business KPIs.

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

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.

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.

Lead end-to-end delivery of large-scale, technically complex customer programs for Phaidra's industrial AI control systems. Own program strategy, customer relationships, cross-functional coordination, risk mitigation, documentation, and continuous process improvements while mentoring TPMs and aligning product and engineering to customer needs.