Top Remote Machine Learning Jobs in St. Louis, MO

The Global Process Owner for S&OP leads the design and continuous improvement of the S&OP process, ensures collaboration across functions, and drives digital transformation and automation within the organization.

Lead cross-functional technical programs, coordinate launches, develop scalable processes and KPIs, manage risks and intake prioritization, influence product and technical strategy, and drive timely delivery with engineering and business stakeholders.

Senior Business Systems Analyst to define requirements for agent-facing servicing applications, design integrations/APIs with core banking systems, translate needs into user stories and acceptance criteria, improve agent workflows and productivity, and identify AI/ML opportunities for fraud detection, automation, and operational analytics. Supports testing, validation, and releases.

Lead cross-functional technical programs from planning through delivery. Coordinate engineering, architecture, and business teams to launch capabilities, manage risks, prioritize intake, define KPIs and processes, influence technical strategy, and ensure timely delivery of large customer-facing initiatives.

Gather and document functional requirements for agent-facing servicing applications, define integrations/APIs with core banking systems, consult with stakeholders, identify AI/ML opportunities (fraud, KYC, automation), support testing and implementation, and act as SME while managing risks and compliance.

Design, build, and deploy conversational agents using Microsoft Copilot Studio. Gather stakeholder requirements, implement NLU/NLP, integrate with enterprise systems, test and refine agents, and provide documentation and user support for HR, policy retrieval, and procure-to-pay automations.

Design and implement conversational AI solutions using NLP, ML, and LLMs. Build ETL pipelines and integrate relational and NoSQL databases. Develop Voice AI interactions on Vertex AI, work with Nuance IVR and Microsoft platforms, and write production-grade Python code.

Lead design, implementation, and scaling of enterprise Palantir data solutions. Oversee cross-functional teams to build data pipelines, integrations, governance, and advanced analytics (ML/AI). Manage project delivery, stakeholder engagement, performance optimization, and mentor senior engineers and analysts while ensuring security and regulatory compliance.

Design, build, and deploy conversational AI solutions on the Kore.AI platform. Create and configure chatbots (intents, entities, dialog flows), integrate with back-end systems and REST APIs, and develop responsive user interfaces using ReactJS alongside UI/UX designers.

Lead digital transformation engagements by developing strategy, advising executives, and delivering end-to-end projects. Drive adoption of cloud, AI, data analytics, and emerging technologies while managing multidisciplinary teams, ensuring compliance, and measuring outcomes through KPIs.

Senior presales role driving planning solution strategy for large enterprises. Lead executive discovery, design tailored demos, articulate value of Workday Adaptive Planning and AI-enabled forecasting, support sales motions (RFPs, workshops, POCs), mentor peers, and travel up to 50% to engage customers and represent Workday at events.

Lead a team of analysts to advance fraud and safety operations through analytics, ensuring robust data products and compliance while empowering stakeholders with actionable insights.

Lead go-to-market strategy for Magnet Forensics' security, incident response, and AI product portfolio. Influence executive, product, and sales stakeholders; translate technical AI/ML and forensic capabilities into messaging; develop buyer personas; create sales enablement and demand-generation content; evangelize products at events; partner with competitive intelligence and customer advocacy; mentor product marketing team members.

Design reusable software tools and subsystems, lead implementation and estimation, ensure systems integration and multi-platform compatibility, drive projects to completion, and perform feasibility analyses for future projects.

Lead architecture and engineering for AI-powered applications across backend, mobile, and desktop. Own reliability, observability, APIs, and model integrations. Grow and mentor a small senior applications team, drive production readiness, and make high-impact tradeoffs across latency, cost, security, and user experience to deliver reliable, low-latency AI-enabled workflows.

Transfyr seeks adaptable builders for various roles across CS, biology, and business. Responsibilities include developing sensor stacks, data harmonization, computer vision, machine learning systems, lab operations, project management, and business development.

Design, develop, and implement AI/ML models; analyze large datasets; integrate AI solutions into existing systems; apply MavLink for autonomous systems; collaborate across teams and improve ML development processes.

Lead the development of production-grade machine learning systems, build ML pipelines, and optimize models for deployment and performance.

Independently validate and monitor machine learning models for credit underwriting, credit risk, and fraud detection. Identify model weaknesses, recommend improvements, and collaborate with model owners to remediate findings. Support and maintain the Model Risk Management framework and coordinate with Internal Audit, Internal Controls, and Compliance on audit and regulatory requests.

As a Machine Learning Engineer II, you will enhance AI systems for automating customer operations, develop evidence extraction pipelines, and collaborate with teams on model development and deployment.

Lead end-to-end data science and AI projects: translate business problems, prepare large datasets, build and deploy predictive/prescriptive and generative AI models (including LLM fine-tuning and prompt engineering), communicate insights to stakeholders, and promote responsible, explainable AI practices across consulting engagements.

Lead AI risk assessments, reviews, and monitoring to support AI governance at a financial institution. Evaluate internal and third-party AI solutions, maintain an enterprise AI inventory, analyze controls and risk metrics, build dashboards and reports, and provide quantitative and advisory support across stakeholders to enable responsible AI adoption and regulatory readiness.

Lead complex transaction monitoring investigations to detect money laundering, terrorist financing, and fraud. Analyze large datasets and payment activity, coach analysts, review investigation quality, improve monitoring rules and processes, collaborate cross-functionally, and support regulatory reporting and audits.

Lead product vision and roadmap for data and analytics products (ML, generative AI, data pipelines, BI). Translate business needs into developer-ready features, maintain backlog, collaborate with engineering and stakeholders, track KPIs, and drive adoption and continuous improvement.

Build and maintain full-stack features, data pipelines, and cloud infrastructure for large-scale ad management and analytics. Integrate with advertising platform APIs, apply ML/NLP for forecasting and recommendations, collaborate with product and marketing teams, and use AI coding tools to accelerate development.