Top Remote Machine Learning Jobs in Spokane, WA

The Director of AI will lead AI and machine learning initiatives, develop AI architecture for humanoid robots, oversee production-ready AI systems, and manage team growth and budget.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

The Research Advisor will provide high-level consultancy for generative AI systems, engage in research collaborations, and represent the Human Frontier Collective in key executive meetings.

Lead a team to enhance Cengage Learning Platforms by implementing AI-first strategies, improving software delivery processes, and ensuring product quality.

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.

Lead and mentor full-stack engineering teams to design, build, test, deploy, and support scalable client-facing and proprietary software. Drive architecture, technical roadmap, Agile delivery, cloud-native migrations, API integrations, quality metrics, and cross-functional collaboration while balancing hands-on development and people leadership to meet product and business goals.

Pre-sales technical role: demonstrate Kore.ai platform, architect and whiteboard solutions, run use-case workshops, estimate ML effort, collaborate with product and delivery teams, and support sales to close enterprise AI and contact-center deals.

Own a Pod's product roadmap: discover customer problems, define initiatives, write high-level requirements, partner with engineering, integrate AI-driven workflows, ensure adoption, track outcomes, and steward product metrics.

Lead pet insurance pricing and state rating plans; build and integrate ML rating models; design pricing strategy for expansion; support rate filings; partner with Data Science, Underwriting, and Finance; and manage and grow an actuarial analyst team.

Lead AI-enabled talent strategy for GTM: workforce planning, people analytics, leadership development, succession management, organization design, change leadership, and coaching senior leaders. Partner with COEs, HRBPs, and People Operations to deploy data-driven HR programs, build leadership bench strength, forecast labor needs, and align performance and rewards to business outcomes.

Own and scale Root's largest enterprise partnerships (OEMs, financial institutions, dealer groups). Drive account strategy, manage a $100M+ pipeline, identify and close new business, lead executive negotiations and contract execution, coordinate cross-functional launches, monitor partnership health, and influence product and commercial strategy to deliver growth.

Serve as the primary product contact embedded with health system clients to discover workflows, design AI-powered solutions, scope pilots, and lead 0→1 deployments. Translate clinical and administrative workflows into product requirements, drive UAT and go-live, measure business success metrics, and surface field insights into the product roadmap. Travel to client sites for discovery and deployment support and collaborate with ML engineers, FDEs, and solution teams to ensure measurable ROI and expansion.

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

Lead strategy and roadmap for DTNs upstream intelligence portfolio, especially Farm Intelligence. Conduct customer discovery, define product metrics, prioritize features, and partner with Engineering, Design, Data Science, and Commercial teams to deliver data-intensive, AI-enabled B2B SaaS products. Drive launches, adoption, and continuous optimization through experimentation, analytics, and stakeholder alignment.

Lead operationalization of AI strategy by implementing scalable AI platforms, standards, and governance. Identify and prioritize high-impact AI and analytics use cases, drive end-to-end delivery into production, embed AI into business processes, manage AI teams, mentor practitioners, and evaluate emerging AI/GenAI technologies to ensure responsible, secure, and measurable business impact.

Research, draft, edit, and validate practitioner-facing US federal tax articles using AI tools. Ensure accuracy and currency, collaborate with data scientists, and align content with tax firm workflows and customer needs while helping build the content function.

Design, develop, and evaluate conversational AI agents and generative AI products. Collaborate with AI scientists, ML engineers, and Responsible AI/Model Validation teams to ensure state-of-the-art, ethical solutions and support deployment and integration of conversational systems.

Senior product leader setting the multi-year Applied Intelligence vision and roadmap for AI-powered B2B AR products. Own end-to-end AI product lifecycle, governance, evaluation standards, talent building, cross-functional partnership, and external representation to drive commercial impact and customer adoption.

The Senior AI Engineer at RegScale designs and operates AI systems, ensuring reliability and performance while overseeing the data pipeline and compliance integration, alongside improving AI capabilities across the engineering organization.

Design and run partner presales enablement programs that build hands-on technical proficiency across ISV and C&SI partners. Own curriculum, assessments, roadmaps, KPIs, and large-scale learning events; coach trainers; align cross-functionally to drive partner-sourced pipeline and certification outcomes.

Lead data science for Root's digital partnerships channel, managing a team to drive growth, profitability, experimentation, forecasting, optimization, and measurement. Partner with cross-functional teams to improve acquisition economics, influence product and technical roadmaps, deliver executive reporting, and establish scalable operating processes.

Develop and productionize computer vision and deep learning models across FloVision’s products. Responsibilities include building ETL pipelines, preparing and annotating datasets, feature engineering, statistical analysis, model training and evaluation, deployment, monitoring, and improving data quality. The engineer will collaborate across machine learning, software, hardware, product, and annotation teams, work autonomously in a startup environment, and occasionally travel to production sites and facilities.

Build and deploy deep-learning models for financial market data, owning the full workflow from raw data and experiments through daily production inference. Responsibilities include managing small-scale GPU infrastructure, conducting leakage-proof and regime-aware evaluations, reproducing research, reading recent AI literature, and communicating findings. The role requires strong ML fundamentals, Python and PyTorch expertise, hands-on infrastructure skills, rigorous experimentation, and self-directed remote work. Trading experience is not required.

Analyze, clean, and validate complex healthcare data; develop statistical, machine learning, and AI models; implement agentic workflows, RAG solutions, and model fine-tuning; deploy and monitor models in production; collaborate with technical and business teams; conduct research; and document and communicate findings.

Develop end-to-end perception solutions for autonomous driving, leveraging deep learning and data-driven approaches to enhance system accuracy and efficiency.