Top Senior Machine Learning Jobs in St. Louis, MO

The Staff Machine Learning Engineer will lead ML systems development for personalization and ranking, design architectures, and mentor team members, ensuring reliable operations at scale.

The Machine Learning Engineer will work on unstructured data classification and clustering, utilizing their expertise in AI systems and various programming languages.

The Senior Machine Learning Engineer will utilize deep experience and insights to enhance communication and digital interactions through advanced machine learning tools and algorithms, focusing on unstructured data.

Design and build scalable data engineering and AI agent governance capabilities across major cloud AI platforms. Develop ingestion, processing, ETL, observability, security, lifecycle management, and identity governance features. Evaluate emerging AI agent frameworks and interoperability standards, troubleshoot customer issues, document architecture and processes, and collaborate with engineering, security, compliance, product, and support teams. The role also involves improving distributed data systems, mentoring engineers, and leading technical initiatives.

The Staff Data Scientist will lead the development and deployment of ML and GenAI systems to detect billing errors and fraud in healthcare payments, collaborating with cross-functional teams.

Drive technical wins for enterprise financial institutions by scoping solutions, leading discovery (MEDDPICC), tailoring demos, building business cases, owning RFI/RFPs and POCs, and coordinating product/engineering to validate feasibility for fraud and financial crime prevention.

Build and maintain ML and generative AI tooling, training and inference platform services, model evaluation and testing frameworks, and APIs to expose ML products. Deploy and manage applications across the AI/ML SDLC, mentor teammates, and write production-quality code daily.

Build and deploy production machine-learning systems within client environments, covering data discovery, modeling, validation, deployment, scheduling, monitoring, and retraining. Develop forecasting and detection models for imperfect time-series data, establish honest evaluation and KPI frameworks, and ship usable APIs or interfaces. Work directly with client IT and data teams through discovery, demos, and feedback cycles. The role also involves data engineering, software development, basic cloud and DevOps work, and advising clients when ML is not appropriate.

Lead machine learning initiatives, oversee product development, improve execution pace, enhance team reliability, and foster team growth at Hightouch.

The Director of Product Management will oversee the product lifecycle for AI products, focusing on customer collaboration, rapid prototyping, and product strategy. The role involves leading product teams, driving execution, and shaping the product culture.

The SAP Innovation Architect will design SAP automations, mentor engineers, and drive innovation in AI-driven SAP operations, while ensuring scalability and security in integrations.

Act as the technical lead in enterprise sales: run technical discovery, design and deliver customized demos and POCs, assess API/cloud/model fit, address technical objections, support contract negotiations, and relay product feedback to engineering while staying current on AI/ML trends.

Lead backend architecture and implementation for scalable, reliable cloud-hosted web products. Mentor engineers, set standards, integrate agentic AI coding tools, design systems applying ML to large datasets, and balance customer-facing features with technical debt and performance.

Lead the Contracts product roadmap for a B2B healthcare SaaS platform, applying deep reimbursement and managed care expertise. Partner with AI engineers to build contract-understanding models, drive adoption, iterate on workflows, create business cases, and coordinate cross-functionally with Legal, Finance, Sales, and SMEs to ensure compliant, revenue-aligned contract execution.

Own end-to-end computer vision and machine learning projects for power grid infrastructure, from problem framing and research experimentation through production deployment and monitoring. Develop detection, segmentation, classification, anomaly detection, and foundation-model solutions; build data pipelines, serving systems, experiment tracking, and model versioning. Conduct error analysis, benchmarking, tuning, code reviews, and testing while translating client requirements into reliable production models and communicating technical decisions and limitations.

Build and improve machine learning systems for ad ranking, relevance, and optimization. Responsibilities include developing active learning and LLM-assisted labeling workflows, owning experimentation and evaluation, and deploying low-latency inference services. The role partners with product, data, and platform teams to improve advertiser performance and user engagement while ensuring production reliability, scalability, latency, and data quality. Candidates will use Python, Go, AWS, distributed systems, and AI-assisted development tools.

Lead the development of deep learning models for email data, optimize models, design evaluation frameworks, integrate products, and mentor junior researchers.

Lead strategy, roadmap, and delivery for Tekmetric's SaaS product for auto repair shops. Own user research, AI/ML product initiatives, cross-functional alignment, go-to-market coordination, and measurement of business outcomes. Train internal teams and iterate on features from concept through launch and optimization.

Lead full sales cycle to drive CTV performance advertising growth in North America: prospect, close, launch and scale CTV budgets, manage key advertiser relationships, collaborate cross-functionally, represent Jampp at events (20% travel), and provide local feedback to improve global initiatives.

Senior Business Systems Analyst responsible for capturing functional requirements for agent-facing servicing applications, defining integrations/APIs with core banking systems, translating needs into user stories and acceptance criteria, supporting testing and releases, analyzing workflows to improve agent productivity, and identifying AI/ML opportunities for fraud detection and automation.

Lead end-to-end enterprise customer engagements and onboarding for large insurance clients, run program timelines and executive reporting, design and deploy AI agents and internal tooling, own the CE operations roadmap and knowledge base, drive cross-functional resolution of technical/operational issues, and continuously improve efficiency and quality across the Client Engagement team.

Design, build, and scale backend systems and APIs for high-transaction consumer products. Collaborate with product, credit, compliance, support, and analytics teams. Contribute to code reviews, technical planning, security, and operational excellence. Mentor peers and promote engineering best practices.

Design, implement, and scale ML-based solutions for search and advertising; define data collection, evaluation, and production serving strategies; analyze data to inform development; communicate cross-functionally; produce technical reports; and stay current with advances in LLMs, vision models, and generative AI.

Industry Expert who reviews and defends advanced AI/ML and systems engineering projects, chairs architecture and executive review panels, hosts occasional technical sessions, and sets standards for instructors. The role requires production-scale engineering experience, live architecture critique, a public technical footprint, strong English, and expertise in agentic systems, LLM evaluation, model serving, cloud infrastructure, distributed systems, observability, RAG, and enterprise deployments.

As a Senior Machine Learning Engineer, you will enhance diffusion models, conduct research, collaborate on system implementations, and communicate findings effectively.