Top Machine Learning Jobs in Kansas City, MO

Lead advanced machine learning research and development, focusing on optimizing models, particularly language models, while mentoring junior team members.

As a Machine Learning Engineer at CompanyCam, you'll work on impactful ML projects, collaborate with cross-functional teams, and leverage Python and SQL for data-driven decisions.

Lead the Relevance and Personalization team to develop end-to-end machine learning systems, applying advanced algorithms across various data types to enhance search and recommendation functionalities at Airbnb.

The Senior/Staff ML Engineer will lead AI/ML projects, focusing on LLMs, design scalable systems, mentor team members, and stay abreast of AI advancements.

The role involves developing advanced multimodal customer experiences using AI, mentoring others, and refining AI processes for Zillow's platforms.

Seeking a Head of Core ML Products to lead the development of AI-driven systems for improved product matching and user experience at Fetch, requiring extensive product management experience.

As a Senior Software Engineer, you'll develop AI-powered solutions, integrate LLMs and AI services into healthcare systems, and mentor team members.

Lead development of data pipelines and workflows for ML models, design scalable data processing environments, and ensure high data quality.

The Senior ML Engineer will design and deploy large-scale ML systems for personalized recommendations, directly impacting user engagement and revenue. Responsibilities include building models serving 100M+ predictions daily and optimizing data processing pipelines.

The role involves building and optimizing large-scale ML systems for personalized recommendations that drive engagement, retention, and revenue, impacting millions of users daily.

As a Senior ML Engineer, you will develop and optimize ad algorithms to enhance engagement and revenue, collaborate with teams, and implement scalable ML systems.

The role involves building and optimizing machine learning systems for ad performance, collaborating with teams to enhance targeting and revenue. Responsibilities include developing algorithms, conducting experiments, and improving infrastructure for scalable ad decisioning.

Lead the development and deployment of scalable machine learning models for fintech applications, collaborating with various teams to meet business objectives.

The role involves leading ML/AI solutions, managing technical roadmaps, collaborating with stakeholders, and driving innovation in products and services.

Design and deploy machine learning models for core product features, optimize home recommendations, and enhance the user experience at Zillow.

Design and architect AI/ML solutions, build document parsers and classifiers, maintain AI systems, and collaborate with cross-functional teams.

The Machine Learning Engineer will build and scale ML models, collaborate with cross-functional teams, and improve real-time recommendations for Stitch Fix's clients.

The role involves designing and scaling ML infrastructure for LLMs, including building training pipelines and deploying models in cloud and on-prem environments. Collaboration with engineers and managing GPU/TPU workloads is key.

The Applied Scientist will integrate LLMs into production systems, develop NLP and CV models, and lead AI initiatives for wealth.com.

The Software Engineer will develop machine learning infrastructure, optimize models, and create tools for data analysis while collaborating with a diverse team.

The Senior Machine Learning Engineer will design and maintain ML solutions for fraud detection, collaborating across teams and establishing MLOps best practices.

Develop, optimize, and deploy scalable ML solutions for content decisions at Netflix, utilizing advanced ML techniques and collaboration with teams.

Design, build, and scale ML systems for demand forecasting and vehicle positioning. Collaborate with teams and mentor engineers to enhance ML expertise.

As a Machine Learning Engineer, you'll optimize and deploy production ML models, build inference services, and collaborate closely with teams to integrate new models and enhance performance.

The ML/AI Engineer will define machine learning direction, develop automated pipelines, integrate models, and collaborate with product teams to solve user problems.