Top Machine Learning Jobs in Vancouver

Build and modernize production full-stack applications across frontend, backend, APIs, integrations, and cloud-native infrastructure. Design microservices and event-driven systems, implement testing and CI/CD, and integrate AI, ML, and LLM capabilities including RAG and agentic workflows. Apply algorithms and quantitative methods to product problems, evaluate models in production, collaborate with cross-functional teams, and mentor developers.

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.

Build infrastructure and tooling for AI evaluation, including distributed execution, task-set validation, graders, human-review calibration, statistical reporting, online feedback loops, and offline-to-online analysis. Partner with product, engineering, data, and ML teams to create reliable evaluation workflows that support faster, statistically sound AI product decisions.

Build infrastructure and tooling for AI evaluations, including distributed scoring engines, task-set validation, grader systems, human-review calibration, statistical leaderboards, online feedback capture, and offline-to-online evaluation loops. Partner with product, engineering, data, and ML teams to deliver reliable, observable evaluation workflows that support faster and more trustworthy AI product development.

Leads technical direction for GitLab’s Core DevOps services, covering CI, CD, planning, and source control. Defines architecture, quality metrics, migration strategies, and technical roadmaps; addresses systemic risk and complex design decisions; prototypes and writes code when needed; partners with Infrastructure, Security, SRE, and Product; adopts AI capabilities; mentors senior engineers; supports incident response and senior technical hiring.

Develop data science solutions for payments across Square and Cash App. Build AI-powered tools, ETL pipelines, dashboards, machine learning models, experiments, and cloud data systems. Partner with Product, Engineering, Finance, and Operations to improve payment success, cost efficiency, risk mitigation, and decision-making. Translate business needs into practical solutions, research questions independently, and operationalize data processes and infrastructure.

Develop data tools, AI automations, ETL pipelines, dashboards, and machine learning models for payments. Analyze experiments, optimize payment performance and costs, mitigate risk, maintain data systems and cloud infrastructure, and translate business needs into actionable solutions while partnering with Product, Engineering, Finance, and Operations.

Build and operate scalable full-stack software and AI-powered products for IoT-driven physical operations. Responsibilities include defining technical strategy, developing backend services, APIs, frontend and potentially mobile features, transforming AI capabilities into customer products, partnering across functions, leading complex projects, mentoring engineers, and improving engineering standards.

Owns analytics and optimization strategy for advertising revenue across Zynga’s mobile game portfolio. Responsibilities include monitoring performance, diagnosing trends, designing A/B tests, identifying monetization opportunities, partnering with product, analytics, and data science teams, supporting AI and ML models, leading cross-functional initiatives, and mentoring analysts.

Own the vision, roadmap, execution, and quality measurement for Clio’s AI Search platform. Lead engineering and ML teams developing hybrid lexical and semantic search across documents, emails, and records. Improve relevance through ranking, query understanding, embeddings, A/B testing, click-through analysis, and offline evaluations. Coordinate across Clio products while balancing relevance, latency, cost, permissions, and customer AI preferences. Translate customer search needs into measurable product improvements and guide both new product development and platform scaling.

Drive pipeline and revenue growth through digital prospecting, lead qualification, relationship building, and SaaS sales. Engage prospective enterprise customers, manage inbound and outbound leads, use tools such as LinkedIn, 6Sense, Outreach, ZoomInfo, and Salesforce, and collaborate with account executives, sales engineers, channel partners, and marketing. The role includes booking discovery calls, creating opportunities, meeting funnel and pipeline KPIs, and closing transactional deals and upsells.

Designs and owns production machine learning systems for game development and live operations. Responsibilities include querying large-scale data warehouses, exploratory analysis, statistical testing, feature engineering, experimentation, model deployment in cloud environments, and collaboration with engineering and product teams. The role also involves mentoring junior data scientists, communicating insights to technical and non-technical stakeholders, and promoting data-driven decision-making.

Design, implement, test, deploy, and operate highly available distributed services for Azure Monitor at global scale. Build telemetry collection, routing, storage, and data-access APIs and tools; improve reliability, security, observability, and diagnostics; and integrate machine learning and AI-assisted operational capabilities. Participate in on-call and incident response, collaborate across teams, mentor engineers, lead design reviews, and drive architectural alignment.

Own the AI automations platform, including authoring, execution, evaluation, and improvement models. Build high-impact automations, enable product teams to ship efficiently, define platform metrics, and partner with AI engineering on agent infrastructure. The role requires customer discovery, technical decision-making, unit economics, and experience delivering adopted AI products and platforms.

Develop and deploy scalable AI products using LLMs, knowledge graphs, personalization, and predictive analysis. Build reliable AI orchestration workflows, backend services, data pipelines, and cloud-native infrastructure. Architect maintainable systems, evaluate model performance, implement observability and experimentation, and deliver secure, high-availability software. Collaborate with product, design, and ML infrastructure teams while mentoring engineers and translating ambiguous product goals into customer-focused 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 enterprise AI workforce transformation by redesigning operating models, business processes, employee roles, and human-agent collaboration. Designs and deploys AI agents, develops AI literacy and retraining programs, embeds adoption into performance and onboarding systems, and protects employee privacy. Directs readiness assessments, change programs, AI councils, champion networks, global training, stakeholder workshops, and adoption analytics to ensure sustained behavioral change across large organizations.

Build and deliver production AI systems across machine learning, generative AI, and agentic workflows. Design scalable ML and data pipelines, integrate heterogeneous data, evaluate emerging AI frameworks, and deploy secure cloud-native solutions. Collaborate with data science, product, security operations, and threat research teams to deliver customer value. Write and review code, troubleshoot production issues, measure AI quality, document technical decisions, and mentor engineers.

Own the direction and implementation of Babylist’s personalization domain, including recommendation, search, feed models, custom embeddings, and shared representations. Take ambiguous problems from concept through production, owning architecture, deployment, monitoring, retraining, evaluation, and customer impact. Partner with product, design, and data, establish AI development standards, make cross-team technical decisions, and coach senior engineers while remaining hands-on with complex machine learning systems.

Leads Geotab’s North American channel sales organization, owning revenue, market share, profitability, partner growth, and strategic commercial relationships. Develops partner plans, negotiates agreements, expands the ecosystem, enables resellers and strategic partners, and aligns channel and direct sales. Builds and manages a high-performing team, oversees hiring and budgets, and applies AI and automation to improve forecasting, productivity, sales processes, and partner effectiveness. Travel of up to 60%, including internationally, is required.

Owns strategic relationships and long-term success for assigned automotive dealership accounts. Develops Customer Value Plans, leads outcome-focused Value Reviews, monitors adoption and account health, forecasts renewals, identifies expansion opportunities, and translates platform usage into measurable business value. The role coordinates with Sales, Product, Support, Enablement, and Implementation teams while representing customer needs internally. Travel to dealerships and customer events may be required.

Leads advanced data analytics for Tribal healthcare initiatives, including data resource inventories, quality assessment, linkage analysis, predictive and prescriptive modeling, reporting, dashboards, and large-scale analytics projects. Establishes data quality frameworks, supports federal compliance, coordinates cross-functional initiatives, and mentors junior analysts. Uses Python, R, SQL, statistical methods, machine learning, and data modeling to produce actionable insights and maintain data integrity.

Leads product strategy, vision, roadmap, and execution for 1Password’s Developer Experience, AI security, and AI-powered security portfolios. Oversees secure developer and AI-agent workflows involving identity, delegation, secrets delivery, and access control. Partners with engineering, design, marketing, partnerships, security, and GTM teams; leads standards and developer engagement; establishes product metrics and operating rhythms; and recruits and mentors senior product managers.

Leads statistical activities for Phase II–III oncology trials from protocol design through results reporting. Provides clinical development, endpoint analysis, SAP, regulatory, safety, and submission support; oversees programming and CRO work; conducts analyses using SAS and R; collaborates with cross-functional teams, sponsors, and health authorities; and mentors junior statisticians across multiple concurrent studies.

Develops machine learning and statistical tools for fisheries catch analysis, modernizes data-processing workflows, integrates and validates large biological datasets, and builds visualization tools for the Sea Around Us database. The role creates end-to-end data science models, establishes reproducible data-quality protocols, provides technical guidance, coordinates research projects, and communicates findings through reports, presentations, and training materials.