Top Machine Learning Jobs in Ottawa

Lead the design and implementation of AI products for edge devices, optimizing machine learning models under edge-compute constraints. Work with petabyte-scale sensor, video, text, diagnostic, transaction, and location data; collaborate with ML, firmware, hardware, and full-stack engineers; prototype new AI experiences; ship production systems at scale; and mentor ML engineers.

Own the strategy, roadmap, and results for AI-powered marketing products, including discovery, content, campaigns, websites, email, social, and attribution. Lead cross-functional collaboration with engineering, design, AI/ML, client success, and sales. Run customer betas, improve product quality, drive adoption and retention, build business cases, and connect marketing channels to measurable revenue outcomes.

Leads GitLab’s Product, Sales, and Finance Data Science teams, managing managers and a 12-person organization. Sets data science standards, prioritizes investments, partners with executives, drives product adoption and revenue growth, and oversees experimentation, causal inference, predictive modeling, and AI initiatives. Develops talent, builds succession, and collaborates with Analytics Engineering and Data Engineering on a shared data and AI roadmap.

Owns quality assurance for cryptocurrency and sanctions compliance programs, including sampling, decision reviews, metrics, risk reporting, corrective actions, and continuous improvement. Partners with BSA/CFT and Sanctions program owners and leadership to ensure compliance standards align with regulatory requirements and product growth. Requires deep AML, KYC, sanctions, and fintech compliance expertise, strong analytical and communication skills, executive influence, and AI fluency.

Build and improve Confluence AI experiences across frontend, backend, and AI integrations. Own features from design through launch, apply generative AI, retrieval, agents, and evaluation techniques, create automated quality testing, monitor production performance, run adoption experiments, and collaborate cross-functionally. Mentor engineers and contribute to architecture, observability, testing, safeguards, and scalable software delivery.

Leads AI transformation, governance, quality oversight, risk management, and responsible adoption across Pfizer Global Supply and QSEO. Establishes GxP-compliant AI lifecycle practices, inspection-readiness frameworks, governance forums, portfolio monitoring, inventory management, metrics, and reporting. Advises senior leaders on AI regulations, deployment risks, investment priorities, and compliance while leading cross-functional initiatives and influencing stakeholders across Quality, Digital, Operations, and R&D.

Leads GitLab’s Product Data Science team, setting its strategy, roadmap, analytical standards, and priorities. Partners with Product and Engineering leaders on experimentation, causal inference, analytics, and production modeling. Manages, hires, coaches, and retains data scientists while building a high-performing function. Provides hands-on technical review of models, analyses, and queries, and communicates insights and risks to senior leaders.

The Data Scientist will partner with Sales, Revenue Operations, and Finance to analyze GTM performance, build and productionize machine learning models, conduct experiments, forecast outcomes, and identify growth opportunities. Responsibilities include statistical analysis, causal inference, Python and SQL development, MLOps, agentic workflow automation, semantic-layer contributions, executive reporting, and communicating insights to nontechnical stakeholders in a fully remote environment.

Build trusted technical relationships with enterprise customers, troubleshoot Samsara hardware, software, APIs, and AI solutions, and optimize implementations. Serve as the primary technical contact, manage incident communications, identify growth opportunities, maintain account records, and collaborate across stakeholders. The role also supports Technical Account Management team development and requires occasional customer travel plus after-hours or weekend coverage when needed.

Own company-critical technical problems and long-term strategy across multiple organizations. Architect scalable customer-facing systems and platforms, remain hands-on in software development, influence senior product and engineering leaders, establish engineering standards, and drive responsible AI adoption in products and workflows. The role requires deep expertise in large-scale software systems, consumer products, distributed systems, and production ML and LLM applications.

Own end-to-end analytical problems across risk, fraud, growth, and lending products. Develop strategies, monitor portfolio and macroeconomic trends, build metrics and analytical frameworks with Engineering and Machine Learning teams, and influence product, regulatory, compliance, and launch decisions. Engage external partners, translate complex insights into action, create AI-assisted workflows, and mentor junior analysts.

Lead Block’s global Workforce Optimization function across customer-facing and regulated operations. Establish strategy for forecasting, capacity planning, staffing, real-time management, analytics, automation, and vendor governance. Build predictive workforce systems, align operational and financial plans, manage risk and compliance capacity, oversee incidents and escalations, and develop a multidisciplinary global team supporting employees, outsourced partners, and AI systems.

Supports the Fintech course through in-person tutorials on machine learning and blockchain, student office hours, case study evaluation and feedback, and exam proctoring. The role requires strong fintech and blockchain knowledge, effective use of grading rubrics, clear communication, deadline management, and completion of a written examination with a score of at least 80%. The teaching assistant must work in French, be located in Ottawa throughout the course, and have access to a computer, internet, microphone, and webcam.

Leads compliance technology oversight for transaction monitoring, sanctions screening, customer risk scoring, and AI-driven case resolution models. Builds AI-powered automation, governance frameworks, human-in-the-loop controls, real-time monitoring dashboards, data-quality controls, and model performance processes. Partners with engineering, machine learning, policy, regulators, and independent monitors to ensure models and data pipelines are explainable, auditable, exam-ready, and aligned with AML requirements across fiat and virtual currency products.

Leads the enterprise AI governance and risk program, developing governance frameworks, policies, controls, risk assessments, compliance processes, and responsible AI practices. Establishes guardrails for generative, agentic, and machine learning systems; monitors regulatory requirements; oversees governance reviews, metrics, reporting, and remediation; and advises executives and cross-functional teams on AI risk, security, privacy, accountability, and innovation enablement.

Leads the enterprise AI governance and risk program, establishing frameworks, policies, controls, risk assessments, review processes, and responsible AI practices. Advises executives, evaluates generative and agentic AI risks, monitors regulatory requirements, supports compliance, develops governance metrics, and coordinates cross-functional stakeholders across cybersecurity, legal, privacy, engineering, data, and operations. The role enables safe, scalable AI adoption while managing security, privacy, regulatory, operational, and intellectual property risks.

Develop and scale production machine learning models for credit decisioning, including default prediction and approval decisions. Build training, decisioning, monitoring systems, data pipelines, features, and algorithms. Conduct research, develop prototypes, and collaborate with engineering, credit, and product teams to deliver machine learning products from inception through business impact.

Develop machine learning models and detection rules for web security products. Analyze large datasets to distinguish legitimate from fraudulent traffic, improve detection accuracy, support production data workflows, troubleshoot distributed systems, and provide insights that guide product improvements and strategy.

Teach a university course on affective and persuasive computing. Responsibilities involve presenting concepts in affective computing, AI, machine learning, human-computer interaction, emotion recognition, multimodal data processing, persuasive technology, and intelligent interactive systems. The role requires expertise in deep learning, physiological signals, facial expressions, speech, text, multimodal fusion, and related applications, with potential emphasis on serious games, virtual reality, and digital health.

Build and deploy agentic and generative AI copilot and autopilot systems for risk and compliance automation. Own end-to-end ML systems, including data integrations, prompt tuning, orchestration, evaluation, productionization, monitoring, and transformer-based model development. Collaborate with product, engineering, platform, and operations teams to improve fraud detection and analyst productivity. Drive strategic roadmaps and cross-functional programs with significant business impact.

Build and deploy agentic and generative AI systems that automate risk and compliance investigations. Own full-stack ML systems, including data integrations, prompt tuning, orchestration, evaluation, productionization, monitoring, and transformer-based modeling across transaction, graph, text, and profile data. Collaborate with product, engineering, platform, and operations teams while leading strategic roadmaps and delivering scalable production systems.

Designs end-to-end architectures and high-level designs for web security products and features, spanning configuration, reporting, runtime systems, analytics, and attack detection. Collaborates with product management and cross-functional teams to define requirements, guides engineering implementation, presents designs, and contributes security product expertise and technical roadmap direction.

Lead technical design and delivery of AI-enabled solutions for Citco’s Fund Services transformation program. Integrate AWS, cloud data platforms, Sigma, UiPath, Databricks, machine learning models, LLMs, and conversational AI. Establish MLOps, CI/CD, security, responsible AI, and production-readiness standards while owning solution lifecycles. Lead proofs of concept, mentor developers, oversee monitoring and support, and collaborate with technical and business stakeholders.

Designs challenging competitive data science and machine learning tasks, reproducible execution environments, reference solutions, automated tests, and evaluation criteria. Uses Python, statistical modeling, mathematical reasoning, and debugging to assess AI coding agents, identify data leakage and implementation flaws, validate solution correctness, and document methodologies. Requires a verifiable Kaggle Expert-level profile, strong practical programming skills, and the ability to independently test and explain technical solutions.

Lead B2B performance marketing and demand generation for a sales-led growth strategy. Manage paid channels, optimize budgets and ROI, run experiments, analyze funnel and revenue metrics, and partner with campaign, analytics, marketing operations, and external vendor teams. The role focuses on generating qualified pipeline and revenue among enterprise and mid-market technical audiences.