Top Machine Learning Jobs in Ottawa

Leads the ISAC System Verification organization’s test strategy, test management, quality objectives, coverage models, metrics, and risk-based validation. Drives AI-assisted testing, automation, continuous validation, and CI/CD-integrated verification for communications and sensing functionality. Partners with systemization, development, requirements, product, and release teams while communicating quality status and readiness to leadership. Coaches engineers, improves verification methodologies, and supports scalable quality practices for current ISAC products and future 6G solutions.

Lead GitLab’s company-wide strategy for autonomous, agentic software development workflows. Identify and validate AI opportunities across the SDLC, build prototypes and reference architectures, establish evaluation frameworks and safety controls, and drive internal adoption. Partner across Engineering, Product, Infrastructure, Security, Architecture, and Data and ML teams to scale reliable, observable, compliant agentic capabilities into customer-facing products. Mentor senior technical leaders and represent GitLab externally on AI-assisted development and productivity measurement.

Leads technical strategy and implementation for RAN software portability across Intel, ARM, AMD, and RISC-V COTS platforms. Responsibilities include architecture alignment, platform onboarding trials, benchmarking, performance profiling, system validation, portability standards, reusable engineering assets, AI-assisted automation, and shared infrastructure readiness. The role mentors distributed teams, represents portability in technical forums, contributes intellectual property, and collaborates with research institutions.

Leads the enterprise IT function across Canada, setting technology strategy, modernizing applications and platforms, advancing AI and automation, and strengthening cybersecurity, infrastructure, and IT controls. Oversees technology roadmaps, budgets, vendors, service management, governance, and portfolio rationalization while partnering with executive stakeholders. Manages IT leaders and develops talent, ensuring technology investments support business growth, operational excellence, security, and digital transformation.

Own the mid-market territory strategy and revenue outcomes across Quebec, Eastern Ontario, and the Maritimes. Generate pipeline, acquire new customers, expand existing accounts, manage sales cycles, forecast accurately, meet quotas, and support renewals. Partner with channel resellers, sales engineering, marketing, product, and renewals teams to deliver cybersecurity solutions, reduce churn, and identify cross-sell and upsell opportunities. Maintain strong CRM hygiene and customer relationships while prospecting and closing competitive opportunities.

As a Staff Machine Learning Engineer, you will enhance credit modeling, manage full credit modeling stacks, and support innovations within regulated banking frameworks.

Lead independent validation and ongoing monitoring of complex financial and analytics models, including ALM, loss forecasting, loan transition, corporate planning, and engagement models. Identify weaknesses, communicate findings, guide remediation, and strengthen model risk governance. Partner with Finance, Quantitative Research, Growth Analytics, Internal Audit, Internal Controls, Accounting, and Compliance on validation, audit, regulatory, and examiner matters.

Lead product strategy for consumer credit, underwriting, merchant pricing, and loan economics. Define features, specs, and metrics; partner with engineering, analytics, design, commercial, legal, and capital to launch and scale products across channels and geographies.

Lead Arondite’s Canadian market expansion from Ottawa by developing defence and public-sector relationships, building partnerships with Canadian primes and technology organizations, qualifying commercial opportunities, and shaping go-to-market strategy. The role combines customer discovery, pipeline development, partnership structuring, pricing, proposals, negotiations, and translating market needs into product and roadmap insights. It requires representing the company with senior government, industry, and partner stakeholders while helping establish Arondite’s long-term Canadian presence.

As a Staff ML Engineer, you'll design and operate Samsara's ML platform, partnering with teams to deliver scalable ML solutions that enhance safety and efficiency in physical operations.

Lead the underwriting and credit risk validation sector within Model Risk Management. Manage and mentor a quantitative team, perform hands-on validations of complex ML models, assess data integrity and model performance, identify and remediate weaknesses, and partner with stakeholders to enhance the enterprise MRM framework and meet audit and regulatory requirements.

Owns marketing analytics measurement across campaigns, channels, attribution, funnel performance, and pipeline forecasting. Builds dashboards, attribution models, AI-powered scoring and insight tools, and executive-level analyses to guide marketing investment. Partners with Marketing Operations, Demand Generation, Events, Sales Operations, Finance, Security, Legal, and Data Engineering. Oversees marketing data quality, develops responsible AI practices, mentors analysts, and supports planning, budgeting, and ROI decisions.

Own Sophos EDR strategy, roadmap, technical product development, AI-powered experiences, and go-to-market execution. Translate customer needs, threat research, telemetry, competitive intelligence, and business goals into product priorities. Partner with engineering, security operations, threat research, marketing, sales, and customer success to deliver endpoint detection, investigation, threat hunting, response, reporting, and XDR/MDR upgrade capabilities while driving adoption, revenue, and customer outcomes.

Serve as the technical sales and customer-facing expert for an AI platform. Responsibilities include conducting product demonstrations, supporting proofs of concept, advising on architecture and development, planning professional services projects, tuning retrieval and agentic pipelines, responding to RFPs, supporting customer adoption, and communicating product feedback internally. The role requires strong AI, cloud, on-premise, application development, storytelling, and enterprise customer engagement experience.

Owns a mortgage origination product substream, including product vision, roadmap, prioritization, workflow requirements, regulatory considerations, release planning, UAT, and issue triage. Partners with engineering, design, QA, operations, underwriting, brokers, advisors, and compliance teams. Serves as the origination subject-matter expert while researching lending trends, regulations, competitors, and AI-enabled opportunities. Uses AI tools throughout discovery, prototyping, delivery, documentation, and measurement.

Own the demand planning product roadmap, translating customer and market needs into forecasting, demand sensing, scenario planning, and AI-enabled capabilities. Lead discovery, prioritization, and delivery with Engineering, Data Science, UX, and go-to-market teams. Define success metrics, monitor performance, represent customer needs, and drive cross-functional alignment. The role requires deep demand planning expertise, enterprise software product management experience, strong analytical and communication skills, and up to 20% travel.

Lead applied AI and machine learning innovation for supply chain products. Develop prototypes and proof-of-concepts, evaluate emerging techniques, and guide promising ideas toward scalable enterprise capabilities. Provide technical leadership across research, product, and engineering teams while remaining hands-on with ML, generative AI, agents, LLMs, optimization, recommendation, and explainability. Influence architecture and technical direction, mentor colleagues, assess AI-generated code, and ensure solutions meet quality, security, maintainability, and customer-impact standards.

Lead cross-organizational technical strategy and execution for core sharing and collaboration systems. Architect and implement foundational frontend/backend and platform solutions at massive scale, drive AI/LLM adoption, mentor engineering leaders, resolve systemic bottlenecks, and remain hands-on in critical design, prototyping, and code contributions.

Evaluate AI model outputs on data science, statistics, machine learning, experimentation, and quantitative problems. Develop expert prompts, datasets, and reference solutions; identify statistical and methodological errors; and provide structured feedback to improve model performance. The role requires Python, machine learning, statistics, data analysis, experimentation, Pandas, and data modeling skills.

Own the full product lifecycle for AI-native insurance agencies and loss prevention services, spanning customer experiences, internal tools, automation, and integrations. Rapidly prototype MVPs with AI-assisted tools, define success metrics, analyze quantitative and qualitative feedback, align cross-functional stakeholders, and ensure regulatory and data security compliance. The role reports to the CEO and requires autonomous product ownership in a fast-moving startup environment.

Manages science and technology initiatives for sustainable industrial fisheries. Leads multidisciplinary projects involving electronic monitoring, AI, machine learning, computer vision, data systems, hardware, software deployment, and seafood traceability. Oversees vendors, contractors, budgets, procurements, technical assessments, and deployment of systems in remote environments. Translates technical concepts for diverse stakeholders and supports technology evaluation, scaling, and conservation strategy. The role may require domestic and international travel of 25% or more.

Develop and deploy statistical and machine learning models for credit risk, fraud, collections, and marketing. Responsibilities include data exploration, model development, production monitoring, performance analysis, governance, stakeholder collaboration, and communicating insights to leadership. The role requires applying advanced statistics and machine learning to improve consumer finance strategies while maintaining documentation, quality assurance, and version-control standards.

Deploy onsite with strategic customers to understand security and risk workflows, build AI-native solutions, analyze data, and integrate SecurityScorecard with enterprise systems. Design cloud architectures across AWS, Azure, and GCP; prototype and productionize software; translate security data into financial risk insights; and maintain technical relationships through renewals and expansion. Travel to customer sites for workshops, technical discovery, and go-live support.

Annotate and manage training/test datasets, run model training, evaluate model performance, perform manual QA and error analysis, and refine annotation guidelines for NLP/ML projects.

Supports responsible AI governance by developing policies, maintaining control frameworks, conducting AI risk assessments, monitoring regulatory compliance, preparing reports, and advising legal, compliance, security, AI, and business stakeholders. The role also tracks governance metrics, supports audits, researches emerging regulations, and recommends improvements to AI governance programs.