Top Machine Learning Jobs in Spokane, WA

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.

The AI Forward Deployed Engineer designs and implements AI solutions, collaborating with stakeholders, enhancing reliability, and producing reusable resources. Responsibilities include diagnosing AI solution issues and engaging with finance and data teams.

As a Staff Machine Learning Engineer, you will optimize Quora's ad products by applying machine learning algorithms, taking ownership of systems, and collaborating across teams.

The Staff Machine Learning Engineer will lead AI initiatives, architect LLM systems, design evaluation frameworks, and mentor engineers.

As a Staff Full-Stack Engineer, you will manage end-to-end experiments, build full-stack product experiences, and drive product and technology experiments with various teams.

The Senior Product Manager will lead ML platform initiatives, collaborate with teams, define success metrics, and develop product roadmaps to enhance platform performance.

As a Machine Learning Engineer, you will develop and deploy adaptive ML systems, collaborate with partners, and lead product strategy.

Lead the Machine Learning Engineering team at AKASA, focusing on improving ML capabilities, model deployment, and infrastructure development, while managing and mentoring engineers.

Design, build, and scale production ML systems (including LLMs) to automate customer support and compliance workflows. Lead technical roadmaps, write high-quality Python code, mentor engineers, ensure secure, scalable architectures, and resolve complex reliability issues.

As a Senior Technical Product Manager, you will lead the AI Platform team to define roadmaps, collaborate with technical experts, and improve healthcare delivery by leveraging AI technologies.

The Staff Advanced Analyst will drive data analytics to improve CS Safety experiences, influence product decisions, and build measurement tools using data-driven insights.

As a Solutions Engineer, you will drive sales growth, support partnerships, and deliver AI-driven solutions while collaborating with various teams.

The role involves leading a team to manage data strategies and analytics for Netflix Games, requiring expertise in data science, business analytics, and team management.

The Brand Marketing Manager will develop content strategies for lead generation, produce high-quality marketing assets, collaborate with the Demand Generation team, and analyze data to optimize campaigns.

Lead the Ad Ranking team, focusing on improving ad quality and performance using machine learning. Responsibilities include team management, stakeholder collaboration, and executing analytical initiatives.

The Product Marketing Manager will execute product launches and support go-to-market initiatives, collaborating with cross-functional teams to develop and deliver messaging and enablement materials targeting both technical and business stakeholders.

The Staff Software Engineer, AI role involves defining technical direction for AI applications, mentoring engineers, and enhancing patient-provider interactions through advanced language and voice technologies.

Lead product strategy and development in cybersecurity, focusing on supply chain security solutions. Engage with customers and cross-functional teams to drive product innovation and performance metrics.

As a QA Engineer, you'll validate features, handle bug fixes, leverage AI for QA workflows, and enhance test automation across multiple product teams.

As Head of Product, you will define the product vision and execute strategy for an AI-driven logistics billing platform, focusing on customer discovery, AI integration, and team leadership.

The Machine Learning Engineer will develop editable visuals combining computer vision and machine learning, enabling chat-driven figure editing and leveraging biological understanding to produce accurate visuals.

The Data Science Actuary role involves building and maintaining rating systems and risk models, conducting analysis for underwriting and operations, and integrating new data sources while collaborating with multiple teams.

As a Data Scientist, you will build predictive models, develop software tools, and analyze geoscientific data to support mineral exploration and discovery.

As a Machine Learning Engineer, you will develop and operationalize models for content understanding and discovery, collaborating with cross-functional teams and stakeholders to solve impactful problems using machine learning.

Lead the Client Solutions team, ensuring the execution of complex transactions while driving innovation and client advocacy. Oversee operations, build client relationships, and implement strategic frameworks for growth.