Top Machine Learning Jobs in Spokane, WA

As a Machine Learning Engineer, you will own the full lifecycle of ML from model development to production deployment, collaborating with teams to drive ML processes.

As a Senior Technical Recruiter for AI/ML, you'll manage full-cycle recruiting for senior AI roles, build talent pipelines, and partner with leadership to close top talent effectively.

NextGen offers an internship for students to learn data science and machine learning. Interns will receive mentorship and work on real projects, gaining skills in Python, ML algorithms, data analysis, and visualization.

Develop and maintain scalable AI/ML architectures, collaborate on integrating solutions into products, and ensure compliance with industry standards.

The Senior Databricks AI/ML Engineer will design and deploy AI/ML solutions in the insurance sector, focusing on Databricks architecture, data pipelines, and MLOps workflows, while collaborating with various teams to operationalize models and optimize processes.

As a Machine Learning Engineer, you will fine-tune transformer models, deploy machine learning solutions, and work with cross-functional teams on innovative projects.

Design and deliver scalable AI solutions powered by Large Language Models. Collaborate with teams to create cloud-native architectures, enable knowledge discovery, and mentor engineers in AI initiatives.

As a Staff Machine Learning Engineer - AI Tech Lead, you will lead the design of AI systems for security operations, focusing on scalable architectures, AI safety, and mentoring. Responsibilities include overseeing technical evaluations, production workflows, LLM fine-tuning, and collaboration with teams to enhance AI capabilities.

The Senior Data Engineer will develop and deploy machine learning models, build end-to-end ML pipelines, optimize performance, and collaborate across teams to enhance AI capabilities at ClickUp.

Design, build, and operate production-grade ML systems for personalization, search, and recommendations. Own end-to-end pipelines from data ingestion and modeling to deployment, monitoring, and iteration, ensuring scalable, reliable, and observable services.

The Senior AI/ML Engineer will design, build, and deploy Generative AI and ML platforms, ensuring compliance and high performance. Responsibilities include developing foundational services, overseeing model training infrastructure, and mentoring junior engineers.

As a Senior Machine Learning Platform Engineer, you'll architect a scalable ML platform, collaborating with teams to ensure compliance, optimize performance, and guide best practices in ML workflows.

Manage AI/ML projects from Proof of Concept to Minimum Viable Product using Agile methodologies while ensuring stakeholder communication and project alignment.

Design, build, and maintain ELT pipelines and analytics-ready data models to support reporting, KPIs, and downstream ML use cases; implement data quality, optimize pipeline performance, document lineage, and ensure governance and privacy.

Lead QA for AI/ML features: design and execute test plans, build Python automation to validate LLM outputs, guardrails, and data pipelines; perform regression, security/privacy validation, and analyze logs/metrics to ensure reliability.

Design and maintain datasets, build and evaluate domain-specific ML and vision-language models for real-time privileged access threat detection; deploy and optimize Python/Docker inference services integrated with WebSocket/WebRTC and protocol-level interfaces; monitor and document production models.

The Senior ML Engineer will develop and optimize machine learning solutions for audience intelligence, build production pipelines, and collaborate with cross-functional teams to enhance user engagement and revenue.

Design and build machine learning models for Zillow's product features, optimize AI components, and mentor engineers within a cross-functional team.

Analyze biological datasets using machine learning and deep learning, collaborate on research projects, and communicate findings through visualizations and reports.

This role involves utilizing predictive analytics to develop customer retention strategies using advanced modeling techniques, data processing, and real-time interventions to improve user experience and business profitability.

The AI Director will oversee ML bot development and implementation, identify AI opportunities, educate teams, and prototype AI solutions.