Top Remote Machine Learning Jobs in Spokane, WA

Lead the development of AI-powered tools and products, manage product roadmaps, collaborate cross-functionally, and drive innovation in media and advertising.

The Staff Technical Program Manager will lead complex product development programs, manage schedules, communicate risks, and advocate for changes required to address business shifts, while influencing teams and stakeholders through various initiatives and maintaining program metrics.

Lead and build the full demand generation function: inbound, outbound-assist, ABM, field, and digital. Own pipeline metrics (MQLs, SQLs, pipeline contribution), run integrated enterprise campaigns, manage marketing tech stack (CRM, MAP, intent, analytics), and align closely with Sales on ICP, messaging, and pipeline quality.

The Data Science Manager will lead and mentor a team of data scientists, drive data-driven decision-making across Stripe, and collaborate with various stakeholders. Responsibilities include managing projects, recruiting, and contributing to broader data science initiatives.

The role involves developing AI technologies for customer support at Airbnb, leveraging ML systems to enhance customer experience through innovative solutions.

Join Nextdoor's machine learning team to build data-intensive products, develop ML models, analyze datasets, and enhance user experiences. Collaborate closely with product and data science teams.

The Principal Architect will lead AI/ML solutions, mentor teams, and collaborate with clients to design and deliver scalable systems using Google Cloud technologies, ensuring compliance with ethical standards.

The Senior Vice President of Underwriting will oversee underwriting outcomes across multiple lines, driving growth and improving loss ratios through data-driven strategies and leadership.

The Hyperscalers and Commercial Lead will develop technology-driven business strategies, drive customer adoption, and manage end-to-end sales processes while working closely with cross-functional teams.

The role focuses on leading editorial efforts to define industry narratives around energy infrastructure, translating regulatory changes into strategic content for executives, and influencing sales and positioning through high-impact communications.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

The AI Executive Partner will advise C-Suite executives on leveraging AI to drive business outcomes, manage member relationships, and deliver innovative AI solutions.

The Senior Director leads research in Application Platforms & AI, guiding clients in AI strategy and market trends, while producing critical research content and engaging with clients directly.

The Senior Display Media Account Manager develops and executes digital media strategies, focusing primarily on Amazon DSP, while fostering client relationships, providing analytics, and driving business growth for clients.

As a P&C Actuary, you will assess insurance risks, review regulatory compliance, support audit teams, and document findings while nurturing client relationships and contributing to practice development efforts.

The Senior Vice President, Data Science & Analytics will lead analytics and data science functions, drive innovation, implement AI, and oversee data strategies across financial services.

Lead product strategy and roadmap for a unified data platform, spanning ingestion, modeling, and an intelligence layer. Partner with engineering and data science to deliver cloud-native pipelines, curated analytic models, and ML productization. Drive governance, metrics, cross-functional alignment, backlog management, and Agile practices to maximize platform value for internal teams and clients.

Manage a portfolio of SaaS customers, build relationships, monitor usage, prevent churn, handle support and troubleshooting, identify upsell/renewal opportunities, and relay customer feedback to product and engineering.

Senior product engineer owning end-to-end product surfaces for a computer vision platform. Ship features from idea to production, prioritize roadmap, design UX details, integrate APIs, improve annotation and model-assisted labeling, and collaborate with engineering and users to drive product impact.

Support AI training initiatives by developing and refining financial models, translating market research and due diligence into structured AI training datasets, and partnering with stakeholders to convert complex financial concepts into training inputs. Evaluate and improve AI-generated financial analyses, identify gaps in modeling or valuation assumptions, and contribute strategic insights to enhance AI-powered private equity tools in a fully remote environment.

Create and curate high-quality graphic design datasets and training materials for AI systems. Collaborate with engineers to evaluate and refine AI-generated visuals, document design processes and style guides, and translate design concepts into actionable training data. Stay current with design trends and communicate feedback to cross-functional teams.

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.

Remote neurologist AI trainer who annotates and reviews clinical data, guides ML model training, interprets neurological diagnostics (EEG, EMG, LP), and communicates clinical insights to interdisciplinary teams to improve AI-driven diagnostic and treatment tools.

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.

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.