Top Machine Learning Jobs in Vancouver

Leads business analysis for AI and automation initiatives by identifying adoption opportunities, developing business cases, gathering requirements, facilitating stakeholder workshops, supporting solution design and delivery, measuring benefits, and contributing to AI governance and continuous improvement.

The AI Security Analyst assesses and mitigates risks across AI systems, machine learning platforms, and Generative AI applications. Responsibilities include threat modeling, vulnerability identification, security monitoring, incident response, root cause analysis, access control, policy development, compliance support, audit participation, and secure design reviews. The role partners with engineering, infrastructure, governance, and business teams to improve AI security capabilities and promote responsible AI adoption.

Translates business needs into AI solution requirements, assesses AI and automation opportunities, develops business cases, and supports solution design and delivery. The role facilitates stakeholder collaboration, testing, implementation, change management, reporting, benefits tracking, and continuous improvement across AI initiatives.

Leads operational oversight, performance analysis, governance, and continuous improvement for AI-powered products and platforms. Develops performance frameworks, executive dashboards, business insights, forecasts, and risk reporting. Partners with engineering, product, and operations teams to improve workflows, support automation, ensure compliance, and drive scalable AI operating models.

Tests and validates AI-powered products, machine learning models, and Generative AI applications. Designs test strategies, executes functional and regression testing, evaluates model outputs, identifies defects, analyzes quality metrics, documents results, verifies compliance, and collaborates with AI engineers and product managers to improve testing practices and release readiness.

Build and operate production machine learning systems for ranking, retrieval, recommendations, search, propensity, churn, LTV, and next-best-action decisioning. Design reliable signal contracts covering freshness, provenance, confidence, eligibility, and calibration. Lead feature pipelines, model serving, experimentation, monitoring, and feedback loops while evaluating fairness, risk, compliance, trust, and long-term customer impact. Collaborate across product, growth, data, platform, modeling, risk, and compliance teams.

Build and operate production machine learning systems for ranking, retrieval, recommendations, search, propensity, churn, lifecycle intelligence, and next-best-action decisioning. Design reliable signal contracts with freshness, provenance, confidence, and calibration guarantees. Lead experimentation, monitoring, feedback loops, and impact evaluation focused on fairness, trust, risk, compliance, and long-term engagement. Partner across product, growth, data, platform, modeling, risk, and compliance teams.

Executes the full CRM marketing lifecycle, including campaign strategy, audience segmentation, personalization, QA, deployment, testing, measurement, and optimization across email, SMS, and push channels. The role manages lifecycle campaigns, uses analytics and automation to improve fan engagement and lifetime value, and collaborates with marketing, analytics, technology, product, agencies, and vendors. English and Spanish fluency, CRM platform experience, HTML editing, KPI analysis, and Photoshop proficiency are required.

Consultative Sales Engineer responsible for driving complex sales opportunities, designing cloud data security and data risk management solutions, delivering proof-of-value engagements and technical demonstrations, advising executive stakeholders, supporting partner channels, and coordinating cross-functional resources. The role requires cloud security, IAM, networking, databases, encryption, privacy, data governance, and strong technical communication skills.

Provides strategic and hands-on biostatistical leadership across pharmaceutical discovery, translational, biomarker, and early research programs. Designs studies, analyzes complex biological datasets, develops advanced statistical methods and reproducible R workflows, and translates evidence into portfolio decisions. The role collaborates with quantitative and scientific functions, supports publications and external partnerships, mentors statisticians, and advances data-driven analytical practices.

Lead the long-term software vision, strategy, and roadmap across machine vision, imaging, AI, machine learning, workflow automation, and 3D products. Influence product managers and align software priorities with hardware, customer, and business objectives. Develop licensing and recurring-revenue strategies, engage customers and partners, evaluate build-or-buy opportunities, and track adoption, revenue, profitability, and satisfaction while ensuring cybersecurity, privacy, and compliance alignment.

Provides workforce management expertise in labor scheduling, reporting, dashboard quality, tool optimization, and business analysis. Conducts time and motion studies, supports process and standard operating procedure improvements, and develops reports and tools for staffing, capacity, utilization, productivity, and performance KPIs. Partners with senior team members to improve workforce planning and supports daily workforce strategy and operations.

Own clinical quality for member-facing AI products by partnering with product, engineering, and clinical teams. Design clinical AI evaluations, define quality thresholds and rubrics, assess accuracy, omissions, hallucinations, medication-safety risks, and translate clinical reasoning into prompts and decision logic. Monitor evolving evidence and standards of care, validate product launches, and communicate findings to technical and clinical audiences.

Owns marketing analytics and measurement across campaigns, channels, attribution, funnel health, pipeline forecasting, and ROI. Builds dashboards, attribution models, AI-driven propensity scoring, forecasting, anomaly detection, and automated insights. Partners with marketing, sales, finance, data engineering, security, and legal to improve the marketing data stack, guide investment decisions, deliver executive reporting, and establish responsible AI standards. Mentors analysts and leads analytical practices across the marketing organization.

Updates machine learning training and test datasets, refines annotation guidelines, initiates model training, and evaluates model performance. The role annotates synthetic text and image data, conducts manual quality analysis, identifies error patterns, reports anomalies, and produces findings on utterance quality, LLM evaluation, ASR bugs, and customer pain points. It also applies basic NLP and linguistic knowledge to ensure data accuracy and consistency.

Serve as the technical SME for compliance automation, overseeing GRC control mapping, evidence collection, integrations, and continuous monitoring. Partner with engineering teams to embed compliance into workflows, support audits and framework rollouts, assign control ownership, reduce audit burden, and maintain audit readiness. Lead cross-functional initiatives and communicate compliance risks, control status, and progress to technical and leadership audiences. The role requires cybersecurity framework expertise, program management, cloud and API fluency, GRC platform experience, and familiarity with AI-enabled compliance workflows.

The Cloud Inference Engineer is responsible for building and maintaining a scalable LLM inference platform, focusing on distributed systems and machine learning technologies while collaborating across teams to optimize performance.

Manage the vision, strategy, and roadmap for Contract Intelligence AI products. Collaborate with teams to define requirements and market strategies, ensuring delivery of generative AI solutions.

Lead development of AI-powered GTM tooling and infrastructure to drive pipeline, conversion, activation, retention, and revenue. Own metrics, run experimentation, partner with Sales/Marketing/Engineering/RevOps, and deliver scalable systems and revenue-compounding platforms.

Lead end-to-end product design for Clio's Fintech/payments area: conduct customer research, frame opportunities, prototype and ship AI-enabled workflows, improve design systems, measure impact, and mentor other designers.

Develop and optimize machine learning and statistical models for fraud detection and anti-money laundering. Analyze large datasets to identify fraudulent patterns, build scalable data pipelines and features, evaluate model performance, and collaborate with engineering, product, and operations teams. Communicate insights to technical and non-technical stakeholders while maintaining data privacy and security compliance. The role offers significant ownership in building Oscilar’s early machine learning stack within a remote-first startup.

Own LanceDB’s product direction by shaping the roadmap with technical leadership, researching users and competitors, gathering continuous user insight, and driving cross-functional prioritization. The role partners closely with engineering as a technically respected peer, defines product changes for AI and data-platform users, uses metrics and experiments to guide decisions, and operates with high ownership in an ambiguous environment.

Research and improve real-time conversational AI for voice drive-thru ordering. Responsibilities include advancing speech, intent, turn-taking, voice activity detection, and order-accuracy models; curating and generating data for rare scenarios; building statistically rigorous benchmarks; evaluating audio and conversational quality under real-time constraints; and translating research into production improvements with applied AI and backend teams.

Own and improve the end-to-end AI engine powering real-time voice drive-thru agents. Design conversational and order-taking logic, address turn-taking and noisy audio challenges, build evaluation infrastructure, and ensure accurate recommendations, substitutions, pricing, and POS integrations across restaurant brands. The role involves researching and deploying new AI techniques, training and productionizing machine learning models, and converting ambiguous quality issues into measurable improvements.

Write and edit accessible journalism about AI for a general audience. Responsibilities include pitching ideas, drafting articles, editing researchers’ and writers’ work, setting editorial standards, and helping launch a consistent media program. The founding editor will shape editorial direction and clarify technical material without oversimplifying it.