Machine Learning Jobs in St. Louis, MO

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Architects and scales enterprise-grade agentic AI and generative AI platforms across public, private, and sovereign clouds. Leads client workshops, defines AI strategies, selects technologies, develops reference architectures, and designs knowledge, security, governance, orchestration, and observability layers. Guides engineering teams from ideation through production, establishes reusable agent frameworks, and manages AgentOps, LLMOps, MLOps, and AI governance while optimizing system performance, cost, reliability, and trust.

Designs enterprise AWS cloud, data, AI, migration, and agentic AI architectures. Supports client pursuits and delivery through presentations, workshops, demos, RFP responses, solution designs, estimates, and technical guidance. Conducts architecture reviews, identifies risks, collaborates with AWS partners and account teams, and develops reusable architecture assets. Requires hands-on AWS implementation and migration experience, infrastructure automation expertise, scripting skills, and an AWS Solutions Architect certification. Travel may range from 0% to 100%.

Supports FP&A and enterprise analytics by developing scalable Power BI reporting, financial models, dashboards, and automated processes. Analyzes financial and operational datasets to identify trends, risks, and opportunities; improves forecasting, budgeting, and recurring reporting workflows using Excel, Python, SQL, Power Automate, and Microsoft platforms. Collaborates with finance, data engineering, IT, and business stakeholders, trains users, maintains governance standards, and contributes to the Pigment planning platform. Evaluates AI-enabled tools to improve reporting efficiency, data quality, and decision-making.

Leads technical strategy and product adoption for major Retail and CPG enterprise accounts as Databricks’ primary technical voice. Partners with account executives, guides customers through data and AI transformations, builds technical champions, aligns solutions to business strategies, and mentors team members. Requires extensive pre-sales, big data, cloud, data science, programming, and production data systems experience.

Serve as a technical SME in AML, sanctions, and third-party risk to support sales and client engagements. Lead RFPs, design API-based integrations, build data pipelines, scope bespoke projects, advise on data modeling and analytics, and drive solution positioning and product feedback across the Americas.

Lead presales for data and AI initiatives: design and present Microsoft Fabric-based data platforms, run discovery and AI workshops, scope proposals, translate technical designs into business value, mentor delivery, and support go-to-market and thought leadership.

As Director of Product, you will define and drive Kobie's data platform strategy to enhance marketing and loyalty programs, focus on AI integration, and develop commercial models.

Design, build, validate, and deploy predictive models using Python and SQL. Apply causal inference, A/B testing, matching models, and AutoML to evaluate interventions. Partner with product and engineering to deliver scalable analytics, ensure data quality and model performance, and communicate insights to stakeholders.

Lead the architecture, implementation, integration, and optimization of Oracle EPM Planning solutions. Design planning, budgeting, forecasting, modeling, security, metadata, and reporting frameworks; configure Oracle EPM modules; and apply AI-driven forecasting capabilities. Lead requirements workshops, testing, deployment, stakeholder presentations, and pre-sales activities. Mentor consultants and developers while advising finance and executive stakeholders on enterprise planning transformation initiatives.

Leads procurement and strategic sourcing across client accounts and properties. Develops sourcing roadmaps, executes eRFPs, manages supplier relationships, audits, performance, contracts, governance, reporting, and cost-saving initiatives. Analyzes market and account data, applies AI and machine learning analytics, supports change management and training, and leads cross-functional improvement projects. The role requires client-facing stakeholder engagement, contract knowledge, analytical ability, and leadership experience in procurement, ideally within facilities-related categories.

Open general application for Rapsodo, a sports analytics company using computer vision and machine learning. Seeking driven team players passionate about sports and technology to contribute to state-of-the-art analytics solutions and growth across product teams. Applicants encouraged to apply to join a fast-paced, innovative company partnered with major sports organizations.

Lead design and build of a cloud-based big data analytics platform: implement analytics infrastructure, integrate streaming and batch data, develop distributed processing pipelines, manage predictive analytics models, and apply machine learning and Bayesian methods. Work involves Scala on OS X and AWS, Java and Clojure, Kafka/Samza, NoSQL, and following TDD, Agile, CI/CD practices.

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 role involves analyzing Synthetic Aperture Radar imagery, curating data for Machine Learning, and recommending strategies based on sensor characteristics.

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.

Design, train, validate, and deploy ML models and production inference pipelines (CV, NLP, geospatial). Build MLOps workflows, scalable APIs, and AWS-deployed AI workloads. Monitor model drift, optimize performance, collaborate with data scientists, architects, and stakeholders, and document processes and integrations.