Top Machine Learning Jobs in Ottawa

Develop, test, integrate, and maintain high-performance L1 embedded software for Ericsson 5G processing platforms and cloud-based RAN environments. Implement physical-layer baseband features across wireless standards and deployment scenarios, troubleshoot complex real-time systems, participate in code reviews and agile practices, maintain test coverage, and document designs and test plans. The role also involves exploring cloud-native optimization and applying AI/ML techniques where appropriate.

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

Lead technical implementation of a market management platform for nodal electricity markets. Design and operate large-scale, data-intensive production systems handling continuously changing data. Make architecture decisions, contribute production software, manage incidents, improve existing systems, and partner with product, engineering, data science, and power-market experts. Lead technical reviews, mentor engineers, and drive optimization, forecasting, and analytical capabilities.

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 scientific and strategic AI efforts for Vaccines Medical: define AI vision and roadmap, govern responsible AI standards, prioritize and deliver validated AI-enabled solutions, partner cross-functionally, oversee deployment and adoption, manage budget and vendors, and ensure regulatory, ethical, and scientific compliance across global medical affairs.

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.

Own vision, strategy, and roadmap for cost-optimization and energy-management products for fleets. Translate telematics and operational data into customer-facing features, run discovery, prototype MVPs, define success metrics, and ship end-to-end with cross-functional teams.

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.

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.

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.

Mine big data to identify actionable fraud insights, develop and deploy product- and channel-specific fraud strategies, optimize fraud rules, monitor fraud trends, investigate emerging threats, and provide executive-level analysis. The role balances fraud loss reduction with customer experience and operational capacity while strengthening analytics capabilities through SQL, Python, automation, and data science tools.

The role involves developing AI-based IDE technologies to improve software development efficiency, collaborating on language and compiler capabilities, and prototyping innovations for developers.

The role involves exploring 6G technologies, conducting research, developing prototypes, and contributing to standards and publications in wireless solutions.

Own the strategy, roadmap, and lifecycle for Assent’s B2B SaaS data network platform. Identify and prioritize market opportunities, develop business cases and requirements, lead discovery and delivery, and collaborate with Engineering, Data Science, Design, Sales, and Marketing. Drive AI-enabled product innovation, customer research, pilots, launches, pricing, adoption, and ongoing product health while navigating complex supply chain, compliance, sustainability, and regulatory requirements.

Lead strategy, vision, and roadmap for a cross-functional squad across Everand and Fable. Drive product development for recommendations, search, and ranking systems, balance experiments and large investments, partner with engineering, design, research, and data to ship features that help readers discover books.

Leads Scribd’s content intelligence and UGC supply portfolio, owning corpus classification, metadata, quality, gap analysis, AI infrastructure, contributor experiences, and content acquisition strategy. Partners with ML, engineering, data science, consumer product, and business development teams to connect content supply with business value. Manages senior product leaders and established engineering and analytics programs while setting portfolio roadmaps and representing content strategy with executives.

Design, build, and operate production ML decision systems to detect and prevent payment fraud, account takeover, identity abuse, merchant/marketplace risk, scams, and other adversarial activity. Own end-to-end production lifecycle: data contracts, low-latency inference, batch scoring, feature quality, deployment, monitoring, incident response, rollback, and feedback loops. Develop AI-assisted workflows and reusable decision capabilities while partnering with modelers, product, compliance, and operations.

Design, build, and operate production ML signal systems—ranking, retrieval, recommendations, propensity, and next-best-action—covering feature/candidate generation, serving, experimentation, monitoring, and feedback. Define signal contracts (freshness, provenance, confidence), evaluate long-term impact (trust, fairness, compliance), and partner across product, data, and risk teams to deliver reusable customer-intelligence capabilities.

Manage and coordinate security projects and operations for the Corporate Security Office, supporting project lifecycle from planning to close-out. Provide data analysis, site inspections, hardware/software testing, security screenings, and policy/maintenance plan development while coordinating stakeholders and technical teams.

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.

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 maintain scalable, reliable ML data platform systems to support dataset generation, model training, analytics, monitoring, and large-scale inference. Collaborate with ML, software, and infrastructure engineers to design cost-efficient data lake and training infrastructure using vendor and open-source tools to enable next-generation ML models.

Lead integration, development, testing and validation of satellite control systems and operations products for a LEO network. Define SOC CONOPS, maintain procedures, support automation and SDP analytics, provide engineering oversight and training to satellite controllers, and manage SCS deliveries and operational performance.

Lead delivery of ML feature platform initiatives: design, build, and operate backend systems for feature creation, storage, backfilling and serving. Collaborate with product, design, and analytics, own quarterly goals, improve platform reliability and code quality, mentor engineers, and support on-call and operational monitoring.