Top Machine Learning Jobs in Kansas City, MO

Design and deploy scalable machine learning solutions using AWS services, collaborate with teams, mentor others, and ensure best practices in data and ML lifecycle.

Lead ML Performance Optimization for autonomous driving, collaborating across teams, implementing optimization techniques, and mentoring engineers for career growth.

Collaborate to scale self-driving systems, build training frameworks, profile model performance, and evaluate emerging technologies for training and inference.

As a Senior Python Engineer at ClickHouse, you will enhance the Python ecosystem for data scientists and ML teams, ensuring efficient data integration and optimizing workflows within the open-source environment.

The Principal ML Infra Engineer will design and maintain scalable ML infrastructure, collaborate cross-functionally, manage technical projects, and mentor team members.

The ML Engineer will leverage deep learning for natural language processing tasks, impacting Entefy's products while requiring strong machine learning fundamentals and NLP expertise.

The Senior Solution Innovation Architect will design and implement AI/ML solutions on the Snowflake platform, collaborate with customers, and provide technical expertise in ML and AI applications.

The Staff Data Scientist will develop predictive models, optimize supply and demand, perform testing, and mentor junior data scientists using advanced data science techniques.

Develop and optimize deep learning models for trajectory generation in autonomous vehicles, focusing on planning, control, and real-time inference.

The Senior ML Engineer designs and develops advanced machine learning models, collaborates with teams, monitors model performance, and implements MLOps practices for scalability.

The Machine Learning Engineer develops and deploys ML models, collaborates across teams, and enhances a coding engine for health care providers.

Lead a team of ML Engineers to develop technology for healthcare, emphasizing hiring talent, technical leadership, and collaboration with stakeholders.

Design and implement machine learning perception systems for autonomous ground vehicles. Work on deep learning models, optimize for edge devices, and collaborate across teams.

The Machine Learning Scientist will design and evaluate algorithms for media processing, collaborate with cross-functional teams, and expand expertise in computer vision and related fields.

Develop innovative machine learning algorithms, build production models for various applications, analyze complex datasets, and collaborate on cross-functional projects at NVIDIA.

Lead the development of ML algorithms for robotic manipulation, focusing on multimodal perception and real-world deployment, integrating with other robotics functionalities.

Work with the product team on automating data ETL pipelines, deploying ML models, and connecting ML models to user interfaces. Collaborate with cross-functional teams on product development.

Lead architectural vision and development of scalable infrastructure for self-driving technology, mentoring engineers and overseeing complex projects.

Design and build ML infrastructure components for autonomous vehicles, ensuring scalability and robustness for high-volume data processing and model training.

The Staff AI/ML Engineer will design and build AI-powered services, develop machine learning models, and optimize workflows, collaborating across teams to deliver quality solutions.

As an ML Solutions Architect, design, implement, and lead machine learning solutions for Conversation AI, collaborating with cross-functional teams to address complex business challenges.

The Senior Machine Learning Consultant designs and develops machine learning solutions while mentoring team members and collaborating with clients. Responsibilities include conducting R&D on AI/ML models, optimizing model performance, and ensuring adherence to ethical AI practices.

As a Staff Machine Learning Engineer, optimize card pricing models, lead ML lifecycle, collaborate with experts, and enhance predictive features.

The role involves building ML infrastructure, creating data pipelines, ensuring data quality, and collaborating with data scientists to optimize models.

As Principal Engineer, lead the development of AI agent systems for ML infrastructure. Oversee team management, architectural vision, and technical contributions while ensuring projects meet productivity metrics.