Top Machine Learning Jobs in Kansas City, MO

Lead the design and implementation of simulation-based validation strategies for autonomous systems, mentoring engineers and ensuring performance metrics are met.

The Staff Data Scientist will lead predictive solutions development, collaborating with multiple teams to drive business outcomes through AI/ML model implementations.

Lead a team of Computer Vision and Machine Learning Engineers, driving the development of models for 3D dental platforms and implementing best MLOps practices.

Lead the Machine Learning Platform team at Coinbase. Responsibilities include managing engineers, collaborating on roadmaps, coaching, and ensuring high system availability.

The role involves deploying machine learning models for autonomous vehicles, developing software for ML runtimes, and collaborating with AI teams.

The Senior Data Scientist will optimize product performance through data analysis, collaborate with teams to provide insights, and support product initiatives.

Lead AI and linguistics teams to develop advanced language technologies, driving innovation and defining the vision for multilingual writing tools.

The Senior Staff Software Engineer will drive infrastructure improvements and build systems to enhance user experience and growth at Coinbase.

As a Machine Learning Engineer, you'll enhance ML productivity, improve model deployment, and implement algorithms for credit decisioning systems.

Analyze and report on data for Enterprise Fraud Operations, develop dashboards and tools, and communicate insights to stakeholders.

Lead AI initiatives at GM, developing comprehensive strategies aligned with business objectives and promoting best practices in a cross-functional environment.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

Lead AI/ML product strategy and execution. Manage PM team, define product vision and success metrics, ensure compliance, and represent Workiva externally.

As a Machine Learning Platform Engineer, you will enhance ML infrastructure, optimize data pipelines, and support ML model performance, addressing user needs and maintaining high-quality code.

The Senior Machine Learning Engineer will develop AI workflows, collaborate with teams on models and pipelines, conduct research, mentor junior members, and innovate solutions for healthcare.

Lead and manage a team of machine learning engineers to develop AI-driven tools for clinicians, ensuring project success and team growth.

The role involves architecting and managing hybrid infrastructure for AI/ML, focusing on Kubernetes, AWS, and Infrastructure-as-Code practices.

As a Senior Machine Learning Engineer, you will develop scalable ML solutions, collaborate with teams, optimize models, and implement best practices for deployments and infrastructures.

Lead a team of Data Scientists and Machine Learning Engineers to develop ML models, drive product strategy and enhance data infrastructure.

The Senior Product Manager will develop risk management strategies, build scalable solutions, manage product roadmaps, and ensure compliance with financial regulations, while leading cross-functional teams.

As a Staff Machine Learning Engineer, you'll define technical strategies, design ML models, implement real-time ML pipelines, and deploy systems at scale to enhance Coinbase's operations and user protection.

Responsible for building globally distributed ML ecosystems, developing data pipelines, implementing microservices, and collaborating across teams to enhance machine learning technologies.

Develop and productionize a next-gen Dispatch System, build ML models, automate processes, and collaborate with various teams while mentoring other engineers.

The Principal Product Manager will oversee AI/ML initiatives, drive product development, translate strategy into technical specs, and manage product lifecycle.

Design and deploy machine learning algorithms, develop production systems, and collaborate with stakeholders to align ML solutions with business objectives.