Top Machine Learning Jobs in St. Louis, MO

The Data Scientist will develop predictive models, analyze geophysical data, and collaborate with geoscientists to enhance exploration programs, focusing on mineral deposits.

The Senior Product Manager will lead product initiatives, manage the product lifecycle, and ensure solutions meet customer needs while driving market growth and achieving KPIs.

As Software Engineering Manager, you'll lead a team in enhancing content workflows through automation and AI, develop scalable solutions, and manage cross-functional collaboration.

The Senior Product Manager will lead the integration of machine learning into search relevance, defining product vision and collaborating with teams to enhance ecommerce search functionality.

Lead the Data Platform & ML Ops team, overseeing data infrastructure and ML lifecycles, mentoring engineers, and driving product innovations.

The Forward Deployed ML Engineer will integrate AI/ML models into clinical software, assist in model fine-tuning, and engage with clients to ensure success in healthcare deployments.

The AI/Machine Learning Engineer will develop systems for automating health benefits decisions, integrating large language models with rule-driven patterns, and ensuring compliance with regulations.

The Machine Learning Engineer will develop software solutions, optimize data pipelines, and deploy machine learning models using cloud platforms and best practices.

Drive delivery excellence and customer success by leading the architecture and implementation of AI/ML solutions while ensuring account growth and client engagement.

The position involves driving AI/ML product development for personalized experiences, partnering across teams, and launching impactful products.

You will build and own end-to-end ML systems, focusing on training, evaluation, deployment, and integration with applications, while ensuring quality and efficiency.

The Senior Machine Learning Engineer will build and own production ML systems, manage end-to-end workflow, debug issues, and mentor others.

The Staff ML Platform Engineer will enhance Afresh's ML platform performance and scalability, collaborating with ML teams to improve systems and deploy models efficiently.

The Principal Data Scientist will design, develop, and deploy machine learning models, innovating methodologies and collaborating across teams to enhance financial decision-making and risk management.

The Forward Deployed Engineer collaborates with clients to solve complex problems using technology, integrating systems, writing production code, and leading projects to deliver impactful solutions in areas like financial crime prevention and national security.

As a P&C Actuary, you will assess risks for insurers, support audit teams, and maintain compliance with regulations, while growing client relationships and improving tools for efficiency.

As a Senior Machine Learning Engineer at ZoomInfo, you will enhance core datasets through ML/NLP solutions, manage entity resolution tasks, and drive cross-functional impact by mentoring teams and collaborating on ML KPIs.

Senior AI/ML Engineer responsible for designing, building, and deploying AI/ML systems, mentoring teams, and leading cross-functional collaborations to drive AI solutions.

The Staff Software Engineer will build and scale machine learning systems for personalization, collaborating with teams to enhance project quality and performance.

The ML Engineer will contribute to the automated discovery engine, developing RL frameworks, synthetic data engines, and evaluating performance using proprietary datasets.

The role involves developing ML models for search and recommendation, collaborating across teams, and managing data pipelines to optimize business objectives.

As a Machine Learning Engineer at Shipwell, you'll build and scale AI-powered logistics solutions, maintaining data pipelines and ML infrastructure across the organization.

Seeking a Senior Machine Learning Engineer to design and implement ML systems, optimize deployment, and collaborate with data teams, focusing on scalability and performance.

Design and develop AI capabilities and scalable microservices. Collaborate to integrate AI models and ensure performance in cloud environments.

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