Top Senior Machine Learning Jobs in St. Louis, MO

Lead the development of innovative AI solutions, guide teams through complex challenges, and collaborate with diverse stakeholders to enhance operational effectiveness and achieve strategic objectives.

The Senior Product Manager will oversee the strategy and development of telematics data products, manage cross-functional teams, and ensure product viability and market alignment through customer insights and technical fluency.

Lead Machine Learning Operations initiatives by developing retail-specific models and a user-friendly Model Workbench for marketers. Ensure product development aligns with customer needs.

The AI Engagement Manager will foster relationships with top partners, facilitate adoption of AI solutions, and analyze performance using BI tools.

Lead the product vision, strategy, and execution for Consumer Risk within Checkout at Affirm, focusing on credit decisioning, pricing, and fraud prevention while managing a team of Product Managers and collaborating with various functional teams.

Lead the design and implementation of ML training systems, manage a team, promote engineering culture, and drive product development.

The Engineering Manager will lead a team in developing a Dispatch Optimization platform, focusing on data science, ML engineering, and operational efficiency, while fostering talent and ensuring project delivery.

Provide technical pre-sales support for SailPoint, managing proof-of-concept processes, architecting solutions, and developing custom code for identity management.

As Principal Product Manager for the Agentic Platform, you will set the vision and strategy for AI infrastructure, drive product development, and facilitate adoption across teams.

Lead engineering teams to design and implement core voice AI APIs. Responsible for team management, project planning, technical strategy, and collaboration with research and product teams.

Manage a team of ML engineers to build and optimize Affirm's economic decisioning engine using advanced ML techniques. Collaborate across teams, provide technical leadership, and mentor engineers while driving a cohesive long-term ML strategy.

Lead development of a greenfield data product by partnering with customers and product teams to build analytics and models (simulation, Bayesian networks, optimization, ML). Maintain existing analytics, improve predictive churn models, and translate customer needs into production-grade SQL/dbt pipelines, dashboards, and data-driven product features.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

The Enterprise Account Executive will manage the complete sales cycle, build relationships with senior leaders, and drive platform adoption within data-intensive organizations.

As an Exploitation Specialist/Imagery Scientist, you'll provide expertise in SAR imagery, assess sensor capabilities, and analyze geospatial data to enhance operational intelligence and machine learning applications.

The Imagery Scientist will provide geospatial expertise and analysis to enhance data curation for Machine Learning testing, improve sensor platform integration, and automate scientific processing workflows.

The Senior Technical Architect will lead AI SDLC transformations, create architectural solutions, mentor teams, and drive innovation in regulated industries.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

The role involves leading ML project implementations, designing production-grade ML solutions, and optimizing AI applications for clients while ensuring effective communication and project management.

The Senior AI Engineer will lead ML project implementations, manage client engagements, optimize Generative AI and NLP applications, and ensure production-grade ML solutions.

As an ML Ops Infrastructure Engineer, you will design CI/CD pipelines for ML, maintain deployment systems, and implement monitoring while collaborating with research teams to ensure model quality and performance.

As a Systems Architect, you'll define and drive the infrastructure architecture for AI/ML workloads, design multi-cloud strategies, manage compute orchestration and storage systems, and lead capacity planning, while also collaborating with engineering leadership.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.