Top Machine Learning Jobs in Vancouver

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.

Participants are needed for an AI technology research study, offering compensation up to $600 for ~1.5-2 hours of participation over one week, requiring skills in tech-related roles.

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.

Define and execute Firefox Desktop search strategy across Windows, macOS, and Linux. Own search roadmaps, experimentation, engagement and revenue metrics, AI-powered search experiences, partner commitments, and cross-functional delivery. Balance user experience, privacy, technical constraints, and business outcomes while collaborating with Engineering, Design, Research, Data Science, and Business Development.

Lead end-to-end delivery of large-scale, technically complex customer programs for Phaidra's industrial AI control systems. Own program strategy, customer relationships, cross-functional coordination, risk mitigation, documentation, and continuous process improvements while mentoring TPMs and aligning product and engineering to customer needs.

Own end-to-end customer relationships across Western Canada in Energy, Mining, and Utilities. Drive high-velocity face-to-face engagement with CIOs/CDOs, generate pipeline, move use cases from POC to production, architect account expansion plans, manage complex multi-stakeholder sales cycles, and maintain accurate Salesforce CRM hygiene and forecasting.

Train and operate production machine learning models on Amazon SageMaker using AWS Trainium. Optimize PyTorch code for Trainium compilation, memory, throughput, and distributed training; diagnose hardware, compiler, device, data, and code issues; build cost-aware end-to-end training pipelines; and collaborate directly with client and internal engineering teams to deliver production workloads.

As a Research/ML Engineer, you will translate cutting-edge AI research into product solutions, develop safety and reliability systems, and collaborate with technical teams.

Develop and maintain simulation scenes, implement motion-planning and collision-checking in ROS2/MoveIt2, build perception components for detection and point-cloud processing, write tested C++/Python code, debug software-hardware integration, and participate in code reviews, CI, and agile practices in onsite R&D/production facilities.

Lead strategy and roadmap for EviSmart's AI products for dental labs. Define product scope, metrics, and commercial case; run continuous user research; instrument features for analytics; coordinate with design and ML teams; own decisions, acceptance criteria, and outcomes to drive adoption and revenue.

Lead complex digital projects and programs from initiation through closure for enterprise clients. Manage scope, roadmaps, budgets, resources, risks, delivery methodologies, and client communications. Own AI-enabled delivery guardrails, review gates, workflows, and value measurement. Lead cross-functional teams, facilitate workshops, manage stakeholders, mentor project managers, and support account growth. Continuously improve project management practices through automation, reusable assets, and AI tools.

Lead a team of 4–6 engineers to turn research prototypes into reliable, scalable systems. Establish technical strategy, architecture, and squad-level outcomes; bridge research and engineering; build testing, observability, deployment, and operational practices; mentor engineers and influence hiring and organizational design across the company.

Full-cycle quota-carrying Account Executive selling Bold Metrics' SaaS fit and sizing solutions to apparel brands. Own outreach through contracting, build ROI cases, manage cross-functional coordination, develop outbound strategies, leverage AI to scale workflows, track funnel metrics, and feed customer insights to Product.

Drive product roadmap and KPIs for free-to-play games. Define goals/OKRs, design and optimize in-app features and monetization, run A/B and multivariate experiments (with ML), analyze game economy using BI tools, and iterate on player engagement. Mentor team members and participate in recruitment.

Own production systems for real-time speech AI, including model serving, self-hosted inference, third-party API integrations, scaling, reliability, observability, release infrastructure, and failover. Build backend services and deployment workflows that meet latency, uptime, quality, and cost objectives. Partner with speech, MLOps, platform, telephony, and product teams while providing technical leadership and mentorship.

Drive product strategy and execution for ML-driven geospatial systems: translate research into production roadmaps, own execution frameworks, manage dependencies across data engineering, ML, and cloud teams, lead sprint rituals, and communicate technical tradeoffs and delivery status to senior leadership and external stakeholders.

Build and manage a machine learning engineering team focused on making engineering drawings and CAD data usable for automation. Lead hiring, onboarding, mentorship, performance, technical direction, design reviews, and production deployment ownership. Guide annotation tooling, active learning, synthetic data augmentation, model health, and organizational growth while remaining technically hands-on and partnering across engineering, technical leadership, and business teams.

Analyze microbiome and longitudinal clinical datasets, develop microbiome metrics and biomarkers using statistics and machine learning, create visualizations and reports, draft clinical research documents, support product and study development, and contribute to scientific publications and proposals.

OneSix is seeking motivated professionals for future opportunities in data and AI consultancy. Interested candidates should submit their resumes to stay in touch.

The Data Scientist will design algorithms for insights, structure data, collaborate with machine learning engineers, and analyze datasets to improve workflow automation and product value.

Drive data-informed capital allocation by building financial models (NPV, IRR), applying AI/ML for forecasting and scenario planning, creating build-vs-buy and prioritization frameworks, implementing decision-support systems, collaborating with cross-functional stakeholders, and monitoring post-investment performance to refine allocation models.

Design, implement, and optimize AI-powered solutions to support financial compliance and controls. Monitor GAAP/IFRS adherence, automate controls and reporting, support internal/external audits, and manage complex accounting areas like revenue recognition and lease accounting while collaborating with finance, audit, and technology teams.

Design, implement, and monitor AI/ML models to improve underwriting risk assessment, pricing, and portfolio management. Translate underwriting rules into data models, integrate models into workflows, analyze datasets for risk patterns, build decision-support tools, ensure compliance and fairness, and collaborate with underwriting, actuarial, product, and engineering teams.

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

As an Applied AI Engineer at Luminai, you will design experiments, optimize machine learning models, and enhance AI platforms for healthcare automation.