Top Machine Learning Jobs in Ottawa

Lead and execute IT audits, assess IT risk and compliance (e.g., PCI DSS, PIPEDA), advise business and IT on controls, develop audit plans, report findings to senior management, and help integrate AI into audit practices while managing and mentoring the audit team.

Interns will prototype rapidly, iterate, and contribute to open-source projects at the intersection of AI and cryptography.

The Head of AI will define and execute an AI roadmap, lead research initiatives, mentor the AI team, and collaborate with senior leadership to enhance health technology.

Lead a major product area end-to-end: set strategy and KPIs, define customer personas and market thesis, prioritize features, drive execution with engineering, and align cross-functional stakeholders to deliver high-impact AI-enabled hiring and people-analytics solutions.

Lead Narvar's Promise team of frontend, backend, and data science engineers to deliver AI-driven delivery date predictions. Drive roadmap, set technical direction, maintain quality, hire and grow staff, run hypothesis-driven cycles, and collaborate cross-functionally. Stay hands-on with AI/ML, cloud infrastructure, and engineering practices to improve SDLC and product conversion.

Identify business challenges and translate them into AI initiatives; architect AI solutions using appropriate models, frameworks, and infrastructure; guide data science and engineering teams through proof-of-concept development and deployment; mitigate bias and model drift through monitoring; and communicate an AI vision aligned with business goals.

Lead end-to-end performance creative: ideate, script, produce, and edit ads for paid social, CTV, and emerging channels. Translate performance data into creative direction, manage agency and production partners, and leverage AI tools to accelerate production while raising visual quality and brand standards.

Lead data-driven initiatives by partnering with marketing, product, and BD to inform acquisition and partnership strategies. Design, run, and analyze A/B experiments, leverage machine learning for in-depth analyses, test growth levers, and automate manual processes to improve operational efficiency.

Support business growth by driving data-driven decisions: run analyses, design and analyze A/B tests, define acquisition levers, partner cross-functionally, and automate operational processes.

Own the technical side of deal progression for airline deployments: qualify opportunities, run demos and POCs, author integration and deployment architectures (PSS, APIs, data feeds, DNS, identity, networking), respond to RFPs/security questionnaires, scope SOWs and NFRs, and build reusable demo/reference assets to drive adoption and expansion while liaising between sales, engineering, and customers.

Partner with cross-functional teams to drive data-driven growth: design and analyze A/B tests, leverage machine learning for insights, define acquisition and partnership levers, and automate processes to improve operational efficiency.

Partner with marketing, product, and biz-dev to drive data-driven growth. Design, run, and analyze A/B tests, define acquisition and partnership levers, leverage machine learning for insights, and automate operational processes to improve efficiency and scalability.

Analyze microbiome and longitudinal clinical data, develop biomarkers and microbiome metrics using statistical and machine learning methods, and create visualizations, reports, protocols, and study reports. The role supports research, product development, scientific publications, proposals, and clinical studies while collaborating independently with microbiome experts in a remote-first startup environment.

Build scalable backend platform capabilities, infrastructure, tooling, and ML frameworks for Walmart’s Membership Experience Engineering team. Lead the full software development lifecycle, apply cloud-native architecture, design APIs and resilient systems, integrate AI and machine learning components, conduct design reviews, and ensure deployment, observability, and maintenance. Mentor engineers, influence technical decisions, collaborate with stakeholders, and use data-driven practices to improve engineering productivity and product outcomes.

Lead development and productionization of fraud prediction models (tabular, graph, behavioral). Build scalable feature pipelines, run experiments, integrate models into real-time/batch systems, monitor model and data health, and collaborate cross-functionally to maintain model reliability and performance.

Develop and optimize machine learning and statistical models for fraud detection and anti-money laundering. Analyze large datasets to identify fraudulent patterns, build scalable data pipelines and features, evaluate model performance, and collaborate with engineering, product, and operations teams. Communicate insights to technical and non-technical stakeholders while maintaining data privacy and security compliance. The role offers significant ownership in building Oscilar’s early machine learning stack within a remote-first startup.

Leads Android software development across design, coding, testing, deployment, debugging, and production support. Develops scalable and secure mobile solutions using Kotlin and modern architectures, integrates AI and ML capabilities, conducts code reviews, supports CI/CD and DevOps activities, monitors performance, and promotes engineering best practices. Collaborates with cross-functional teams, owns feature delivery, mentors peers, and contributes to Walmart+ customer-focused platform improvements.

Develops, calibrates, validates, and maintains credit risk models, including PD, LGD, and EAD models, for lending, collections, loss forecasting, capital planning, and stress testing. Analyzes large datasets, evaluates model performance, documents model changes, supports systems testing, and communicates statistical insights to stakeholders and management. Collaborates across the credit union to improve risk-return strategies and reporting.

Lead design and implementation of high-throughput, low-latency programmatic bidding systems. Collaborate with ML engineers to deploy real-time inference, optimize distributed microservices, run experiments and quantitative analysis, and partner with product to ship scalable features. Foster operational excellence, mentor engineers, and continuously improve performance and reliability.

Lead high-complexity data science initiatives improving search ranking, retrieval, relevance, and evaluation. Develop and deploy production machine-learning and NLP solutions, investigate LLM-based ranking features, optimize SQL queries, and work with sparse privacy-preserving data. Define strategies for ambiguous problems, guide other data scientists, collaborate with product teams, and own projects from scoping through production.

Analyze and optimize payment-risk rules, thresholds, customer segments, and manual-review strategies. Use SQL, Python, experimentation, and decision-science techniques to reduce false positives, customer friction, operational workload, and payment losses. Investigate fraud patterns, build monitoring and reporting, evaluate risk changes, and provide practical recommendations while partnering with Risk Operations, Product, Engineering, and Data teams.

Provide teaching support for an undergraduate Introduction to Artificial Intelligence course: contact with students, grading, proctoring exams, and other assigned duties. Must have strong ML knowledge and hands-on proficiency with PyTorch and GPU programming. Selection includes interview; transcripts may be requested for preferred candidates.

Lead Flight Dynamics for the Lightspeed LEO constellation, owning orbital operations, SSA, maneuver and station-keeping strategy, CONOPS across mission phases, team leadership, FD system development, cross-team coordination, and go/no-go operational decisions.

Lead engineering for in-orbit operations of Lightspeed LEO satellites: integrate and validate SatOps systems, develop SOC products and automation, maintain procedures, provide engineering guidance and training, drive telemetry analytics and SDP development, and oversee CONOPS across LEOP and routine operations.

Lead mission planning and execution for LEO orbit raising, station-keeping and disposal. Perform orbit determination, maneuver design, conjunction assessment and collision avoidance. Automate and refine operational workflows, support FDS/SSAS development and verification, mentor junior analysts, and provide operational inputs across LEOP/EOR and on-station phases.