Top Machine Learning Jobs in St. Louis, MO

The Sales Development Representative will identify new business opportunities, qualify leads, and support sales strategies in the U.S. market, collaborating with sales and marketing teams to enhance lead generation and relationships.

Lead the Data & Analytics team, focusing on building data platforms, improving delivery speeds, and integrating Generative AI into data strategies.

The Senior Generative AI Engineer will design and deploy AI/ML solutions, focusing on Generative AI systems and their operational excellence across various sectors like R&D and Clinical Trials.

The Engineering Manager will lead a team of Data Scientists and ML Engineers to build a Dispatch Optimization platform, focusing on model deployment and operational excellence.

As Director of Engagement Management, oversee the team, drive customer success strategies, manage operations, and enhance product utilization while fostering team development and customer relationships.

The Digital Inside Sales Specialist will identify and close digital transformation opportunities in AI, ML, and automation, focusing on B2B sales within targeted accounts while collaborating with internal teams for technical consultation.

The Business Process Consultant will partner with operations to analyze and optimize processes, enhancing efficiency, governance, and customer outcomes. Responsibilities include data analysis, developing process improvements, and supporting change management.

Design and implement machine learning models to solve business problems, analyze data for insights, and optimize model performance.

This role involves leading a perception team in developing algorithms for autonomous driving systems, supervising team members, and conducting research to enhance perception capabilities.

As the Lead AI Strategist, design and deploy advanced AI/ML models to optimize revenue and mitigate medical costs, impacting financial performance directly.

The Senior Product Manager will lead the development of HubSpot's usage data platform, ensuring reliable analytics, defining product vision, and collaborating across teams.

The role involves researching, developing, and implementing AI solutions, optimizing models, integrating AI into workflows, and collaborating with teams to enhance business efficiency.

Lead the Performance ML squad, managing and mentoring engineers while driving the development, deployment, and strategy of predictive models for advertising.

Support and improve the knowledge base and AI-driven systems by curating, validating, cleaning, tagging, and analyzing data. Collaborate cross-functionally, lead a capstone project to reduce queries and improve customer satisfaction, and promote responsible AI practices and governance.

As a Customer Success Manager, you will drive product adoption and retention for customers, build strong relationships, and deliver insights to enhance the customer experience by leveraging data.

The Senior Manager of Product Management leads the transfer pricing software portfolio, focusing on product strategy, customer outcomes, and cross-functional collaboration to enhance product effectiveness and customer retention.

The Azure AI/ML Engineer will design and implement AI solutions on Azure, focusing on automation, security, and compliance in collaboration with various teams.

The AI/Machine Learning Specialist designs and implements AI solutions, collaborates with cross-functional teams, and continuously improves ML processes.

As a Machine Learning Intern, you'll prototype and evaluate ML systems, collaborate with teams, and analyze large datasets to improve user experiences.

Design, develop, and deliver machine learning models for clinical data. Collaborate with stakeholders and optimize production ML systems.

The Data Engineer will build real-time data pipelines for pricing algorithms, collaborate with teams, and contribute to batch data workflows.

The Senior Data Engineer will develop real-time streaming data pipelines for pricing algorithms and machine learning models, ensuring low-latency data delivery and system reliability. Responsibilities include collaborating with other teams, defining architectural standards, and mentoring junior engineers.

Partner with Membership to build data pipelines, ensure membership data quality, and develop predictive models (churn, retention, LTV). Design and analyze experiments, create dashboards, and collaborate with Marketing, Finance, and Product to optimize pricing, offers, and lifecycle programs.

Lead design and delivery of generative AI features end-to-end, prototype and productionize early-stage AI systems, set technical direction, mentor engineers, and collaborate with product and design to drive measurable product impact.

Drive measurement, causal inference, and experimentation to optimize content promotion and personalization. Build robust metrics, partner with product and engineering, surface discovery opportunities, and independently deliver high-impact analytics and ML solutions.