Top Senior Machine Learning Jobs in Spokane, WA

Own product strategy and delivery for chat, voice, and proactive support surfaces to maximize automation rates and CSAT. Build AI-integrated capabilities with ML/LLM teams and vendors, partner with Engineering, CX Operations, Data Science, and Compliance on platforms (Amazon Connect, Sprinklr, Salesforce), drive build-vs-buy decisions, and execute cross-functional delivery to optimize customer and agent experiences.

Serve as second-in-command for Coinbase Derivatives' Market Regulation Department, leading day-to-day regulatory compliance, managing exams and audits, advising on CFTC Core Principles, reviewing surveillance escalations and enforcement actions, and coordinating cross-functional regulatory workstreams to ensure the DCM meets obligations and resolves findings timely.

Provide legal guidance on Rubrik's AI use and products, ensuring compliance with laws and contracts, drafting and negotiating AI terms, coordinating generative AI review processes, educating employees, and improving AI review controls and workflows across cross-functional teams.

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

The Senior Product Manager will oversee the strategy and development of telematics data products, manage cross-functional teams, and ensure product viability and market alignment through customer insights and technical fluency.

Own and execute multi-year strategic partnerships with a hyperscaler and an AI lab, aligning technical integrations, commercial motions, and joint go-to-market plans. Coordinate cross-functional teams, run operational cadences, track measurable outcomes (pipeline, ARR, integrations), and represent partnerships to executives while driving hands-on execution and follow-through.

Design and deploy machine learning models for financial document processing, optimize large language models, collaborate with cross-functional teams, and guide junior peers in a fast-paced environment.

The Senior Staff Machine Learning Scientist will lead research initiatives in computer vision and multimodal understanding, develop novel models, and translate research into practical applications while mentoring team members.

The Senior Machine Learning Engineer will design, implement, and optimize machine learning models, drive AI initiatives, and collaborate cross-functionally to enhance SailPoint's AI capabilities.

Lead end-to-end ML systems for identity verification, including document authenticity, face match, liveness and deepfake detection. Build GNN-based identity graphs, behavioral/device-intelligence models, vendor benchmarking/evaluation, and production enforcement. Mentor engineers and align ML architecture with Product, Compliance, Risk, and Security stakeholders.

Design, build, and deploy production-grade ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM applications, and scalable data pipelines with observability and MLOps practices for cloud and on-prem environments.

Design, build, and deploy production ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM features, data pipelines, observability, MLOps, and containerized deployments across cloud and on-prem environments.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.

The role involves defining the vision and strategy of the Outreach AI Platform, prioritizing the roadmap, collaborating with engineering and data science teams, and engaging with customers to refine AI strategies.

Lead complex, cross-functional AI programs end-to-end: translate strategy into integrated plans, drive multi-team execution, mitigate risks (data, model, compliance), apply ML lifecycle practices, use Agile/kanban methods, manage budgets/vendors, communicate to senior stakeholders, and mentor other program managers to improve AI program standards.

Lead product analytics to improve user growth, engagement, retention, and revenue. Design and analyze A/B and multivariate experiments, perform funnel/cohort analyses, maintain KPIs and dashboards, ensure event tracking, leverage ML and AI tools for advanced analyses, and translate insights into product recommendations across cross-functional teams.

Design and lead end-to-end AI solution architectures, ensuring scalability, security, and compliance. Translate business and regulatory requirements into technical designs, evaluate tools/platforms, document architecture standards, coordinate technical teams, and support deployment and ongoing improvements.

The Sr. Machine Learning Engineer will develop and deploy ML solutions for healthcare, manage data pipelines, and work with large datasets to enhance healthcare delivery.

Lead design, build, and operate an end-to-end Identity Platform for KYC/KYB, overseeing CIP, CDD, sanctions screening, and continuous risk monitoring. Drive AI-first automation to reduce manual reviews, mentor engineers, manage reliability and incidents, and represent technical solutions to customers and regulators. Partner cross-functionally to shape roadmap and ensure regulatory compliance and extensibility across jurisdictions.

Lead a team of safety engineers to define and execute AV safety strategy across development, simulation, testing, and deployment. Apply UL4600/ISO standards, develop safety cases, set safety metrics (SPI), manage safety plans and artifacts, train engineers, and coordinate with partners and stakeholders to validate ML models and ADS integration for safe public-road operation.

Lead product initiatives for football data analytics and AI experiences: define business cases, understand customer workflows, drive cross-functional squads, own in-product onboarding and customer success, and iterate quickly to deliver measurable outcomes like revenue and retention.

Lead product discovery, prioritize roadmaps, and deliver football data analytics and AI features. Work with design, engineering, analytics, and former NFL experts to build, onboard, and iterate products that drive revenue, retention, and customer success in a fast-paced startup environment.

Lead design and scaling of a unified fraud and risk platform. Define product strategy, own fraud metrics, run SQL-driven analysis and A/B tests, and partner with engineers and data teams to build real-time detection, identity verification, and transaction monitoring. Balance customer experience with risk mitigation and communicate impact to executives, legal, and partners.

Own and scale the customer entry-to-purchase lifecycle: design acquisition journeys, build and optimize welcome/abandon/lead conversion automations, implement personalization and gamification, partner cross-functionally, steward list health and deliverability, and run A/B and multivariate testing to improve conversion and engagement metrics.

Lead sales of Akamai's enterprise security portfolio across assigned Midwest accounts, develop and manage pipeline, position Zero Trust architectures, collaborate with internal security engineers and researchers, engage C-level stakeholders, and close new and expansion business.