Top Machine Learning Jobs in Ottawa

As Principal Product Manager, you'll define and execute the strategic vision for AI quality, enhancing enterprise search and AI products through cross-functional collaboration and customer insights.

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 AI-driven automation for risk and compliance by defining strategy, roadmaps, and metrics. Partner with ML engineers, data scientists, design, legal, and operations to build, evaluate, and deploy safe, reliable automations; run experiments, define success/failure behaviors, and drive cross-functional execution to improve decision quality and operational efficiency.

Lead strategy and execution for AI-powered risk automation products. Identify automation opportunities, define product requirements, partner with ML/data/engineering/design, run experiments, set metrics for accuracy, safety, and reliability, and drive cross-functional launches to improve decision quality and operational efficiency.

Lead teams in building end-to-end AI products focused on computer vision and sensor data. Oversee model lifecycle, data management, and deployment. Drive innovation in AI while fostering team development and ensuring customer success.

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.

The Global Head of Sanctions will lead Block's sanctions compliance program, manage escalations, regulatory reporting, and engaging with external agencies while developing and implementing sanctions policies.

Lead a team of ML engineers to develop and improve fraud detection models, defining strategies and fostering collaboration across functions to ensure effective model integration.

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

The Staff Software Engineer will develop full-stack applications, lead projects, mentor teammates, and drive architectural discussions to enhance Toast's restaurant platform.

The role involves teaching a course on high-performance computing algorithms for engineering applications, focusing on programming concepts and implementation with a strong background in mechanical engineering required.

Manage a team of ML engineers to develop machine learning solutions for underwriting applications. Set technical strategy, mentor engineers, and collaborate with teams across the organization.

Evaluate and rank AI-generated Computer Science content for factual and technical accuracy, craft domain-specific prompts and questions, provide expert feedback to improve model reasoning, and support AI training and evaluation workflows on a freelance, remote basis.

Develop and implement chatbots and voice bots using Google Cloud Platform technologies, focusing on Dialogflow CX and related functionalities while collaborating with teams and optimizing performance.

Support FP&A forecasting, budgeting, and rolling forecasts; build driver-based financial models; analyze variances and deliver insights; create BI dashboards; validate data across ERP, Anaplan, and Snowflake; and automate reporting while enabling AI-driven forecasting.

Design, deploy, and maintain end-to-end ML-driven risk solutions at scale to detect and prevent fraud, abuse, and credit risk. Lead technical decisions, build ML tooling and processes, apply state-of-the-art models and third-party data, investigate emerging risk patterns, and collaborate with platform and cross-functional teams to ensure reliable real-time model operation.

Design, deploy, and maintain end-to-end ML risk solutions at scale to detect and prevent fraud, merchant risk, and credit loss. Partner with cross-functional teams, lead technical decisions, build ML tooling, monitor models in production, and investigate emerging abuse patterns to improve detection and decisioning.

As a Senior Machine Learning Engineer, you'll design and develop workflows utilizing vision-language models, manage data pipelines, and collaborate with multiple teams to enhance model accuracy and efficiency.

In this role, you will lead AI personalization initiatives, develop AI/ML models for user experience, collaborate across teams, and ensure rigorous development practices.

The position involves teaching hydrogeology and hydrology, supervising students, developing research, and engaging with industry and government partners.

Lead an interdisciplinary research program investigating mechanistic interactions in psychosis using neuroimaging, computational psychiatry, AI/ML, and multimodal data integration; supervise trainees, obtain external funding, teach, and translate discoveries into precision psychiatry and patient-centred care.

As a Machine Learning Engineer II at Affirm, you'll develop AI systems for automating customer operations and collaborate on building models while ensuring high-quality code production.

Design, build, and operate production ML decision systems to detect and prevent payment fraud, account takeover, scams, and other abuse. Integrate diverse signals into low-latency serving and batch scoring, own feature pipelines and model lifecycle, develop AI-assisted triage and feedback loops, and partner cross-functionally to balance fraud reduction with legitimate customer access.

Design, build, and operate production ML systems that generate trusted signals for ranking, retrieval, recommendations, propensity/churn/LTV, and next-best-action decisioning. Define signal/data contracts, own feature and candidate generation through serving, experimentation, monitoring, and feedback loops, and evaluate long-term business impact, trust, fairness, and compliance. Partner across product, data, modeling, risk, and compliance and apply AI/agents to accelerate engineering and operations.

Independently validate and monitor machine learning models used for credit underwriting, credit risk, and fraud detection. Identify weaknesses, recommend improvements, and collaborate with model owners to remediate findings. Partner cross-functionally to implement and maintain the Model Risk Management framework and support audit, compliance, and regulatory requests.