Top Machine Learning Jobs in St. Louis, MO

Leads responsible AI and model governance while building and deploying healthcare fraud, waste, and abuse models. Establishes standards for documentation, monitoring, bias, drift, validation, and production readiness. Evaluates generative AI use cases, develops policies, validates large-scale claims models, and presents methodology and controls to partners, auditors, and investigators. Works remotely with data scientists, BI developers, and healthcare subject-matter experts.

Own and execute multi-year strategic partnerships with a hyperscaler and an AI lab, aligning technical integrations, commercial motions, and joint go-to-market plans. Coordinate cross-functional teams, run operational cadences, track measurable outcomes (pipeline, ARR, integrations), and represent partnerships to executives while driving hands-on execution and follow-through.

Build and maintain Safari AI’s cloud infrastructure, including production services, system design, reliability, documentation, and security compliance. The role sets technical direction for the cloud stack, collaborates with engineering and operations teams, improves development processes, and delivers incremental features. Candidates should have 4–6 years of software engineering experience, public cloud expertise, and experience taking complex services from concept through production. Streaming processing and machine learning experience are advantageous.

Design, develop, implement, support, and improve financial-system integrations, databases, reporting solutions, and automated processes. Lead technical financial systems projects from requirements gathering through implementation, focusing on Aderant Expert, SQL Server, SSIS, SSRS, and T-SQL. Collaborate with Finance, IS, vendors, and business stakeholders; troubleshoot complex data issues, optimize database performance, document technical solutions, and support multiple concurrent initiatives.

Conduct independent research on frontier AI evaluation and auditing. Design rigorous evaluations, audit methods, and reproducible experimental pipelines; analyze model capabilities, risks, robustness, and alignment-relevant behavior. Produce audit reports, recommendations, publications, tools, and presentations while collaborating with technical, policy, engineering, and standards teams. The role requires careful handling of confidential information and may involve pilot audits with frontier AI companies.

Own Litify’s AI Call Intelligence product line end to end, including call capture, transcription, summaries, conversational insights, voice agents, and agentic workflows. Define the roadmap, quality standards, guardrails, and evaluation practices; lead client discovery, beta programs, competitive research, backlog prioritization, and cross-functional delivery. Partner with engineering, design, data science, and go-to-market teams to launch products, drive adoption, and measure outcomes.

Drafts and prosecutes U.S. and international patent applications focused on quantum computing and emerging technologies. Responsibilities include working with inventors and engineers, preparing Office Action responses, managing patent portfolios, advising on patent strategy, and developing client relationships. Requires substantive quantum computing patent experience, USPTO registration, a technical degree, a JD, and at least three years of patent preparation and prosecution experience.

Leads Sophos’s Americas MSP channel strategy, revenue growth, partner productivity, and operating performance. Oversees recruitment, onboarding, enablement, retention, distribution relationships, recurring-revenue forecasting, strategic negotiations, and program optimization. Builds and coaches direct and matrixed teams while influencing product, pricing, investments, and partner-program decisions. Uses performance data and market intelligence to improve activation, adoption, retention, expansion, and return on investment across cybersecurity managed-service offerings.

Lead client-facing AI program governance and delivery as PMO manager. Translate business objectives into AI roadmaps and OKRs, oversee AI/ML lifecycle, ensure data readiness, model validation, deployment, and responsible AI compliance. Manage PMO standards, portfolio prioritization, AI-augmented reporting, and lead executive communications while mentoring PMs, TPMs, and analysts.

Own and scale the company’s global privacy and data protection program. Advise product, engineering, sales, marketing, security, and executives on privacy laws, data transfers, DPAs, AI governance, security commitments, incident response, and regulatory requirements. Manage privacy assessments, data inventories, notices, training, outside counsel, and vendor relationships. Partner with Security and GRC on audits, certifications, breach response, government requests, and customer obligations while building scalable processes and eventually a privacy team.

Designs and operates production data infrastructure, ETL/ELT pipelines, APIs, containerized AWS services, and graph-based systems. Responsibilities include relational, document, and graph database architecture; data quality and lineage; CI/CD automation; and integration of blockchain, financial, and investigative data. Partners with R&D, data scientists, and investigations teams to deliver production software for federal and commercial clients.

Lead the Personal Loans portfolio strategy, quantitative analysis, risk-based pricing, deal economics, and profitability initiatives. Manage a distributed analytics and portfolio team across New York and Israel, align strategies with partners, and collaborate with Risk, Product, Capital Markets, and Engineering. Translate complex credit and financial analysis into executive recommendations while optimizing customer conversion, risk-adjusted yield, margins, and lifecycle outcomes.

Lead a portfolio of technology-enabled continuous improvement initiatives for internal operations and DoD customers. Manage product backlogs, write user stories, define roadmaps, gather requirements, and facilitate Agile, Scrum, SAFe, and PI planning activities. Drive Splunk analytics, dashboarding, alerting, AI, ML, automation, proactive monitoring, and predictive analytics solutions. Ensure stakeholder alignment, measurable operational improvements, and compliance with DoD security requirements while maintaining an active Secret clearance.

Create end-to-end computer-use tasks for AI agents in Linux desktop environments. Design realistic multi-application scenarios, prepare files and instructions, write Python setup and automated scoring scripts, test tasks, and document them. The contract requires daily check-ins, rapid feedback, and availability throughout a three- to four-week engagement. Experience with AI tools, AI/ML projects, Linux VMs, Git, reinforcement learning environments, or computer-use benchmarks is relevant.

Leads complex AI client projects from requirements gathering through delivery, serving as the primary client contact and coordinating Sales, Operations, Product, and Engineering. Responsibilities include defining scopes and delivery plans, managing risks, quality, timelines, budgets, profitability, and KPIs, resolving execution challenges, and improving scalable processes for AI project delivery.

Leads a data science team focused on customer intelligence and personalization across digital products, apps, newsletters, and marketing channels. Develops lifetime value, segmentation, retention, recommendation, attribution, forecasting, and engagement models. Owns product funnel analytics and experimentation, including A/B testing and causal inference. Partners with Product, Marketing, Editorial, Data Operations, and Engineering to translate customer behavior into product improvements, measurable growth, and scalable data capabilities.

Develops and productionizes deep learning and machine learning perception models for robotics and recycling sortation. Responsibilities include experimenting with neural network architectures, designing computer vision solutions, conducting statistical experiments, deploying successful models, collaborating with data, modeling, and cloud infrastructure teams, and improving ML infrastructure.

Analyze and characterize conversational audio data, identify underrepresented areas, and build active-learning and human-in-the-loop workflows. Develop representative benchmarks, automate model adaptation, and create reusable data analysis and scoring systems. Partner with research, engineering, and data teams to run experiments, improve models, organize data, and translate complex findings into measurable product improvements.

Lead Sardine’s fraud product portfolio, setting vision and roadmap across device intelligence, behavioral biometrics, and machine learning. Manage product managers and partner with engineering, data science, risk operations, marketing, and sales. Drive fraud detection performance, reduce false positives and customer friction, monitor emerging threats, and scale zero-to-one products into enterprise-ready solutions for payment and fraud-prevention customers.

Leads the enterprise data strategy, builds and scales the Data & Analytics team, and oversees data warehouse modernization, migration, governance, KPI standardization, and data quality. Partners with executives and cross-functional teams to convert data into actionable insights, operational improvements, predictive analytics, and AI-enabled workflows. The role requires hands-on Python, SQL, cloud, machine learning, and ETL expertise, plus strong leadership and communication skills.

Leads a data science team and personally drives analyses, experimentation, and product analytics to identify patient experience improvements. Partners with Product, Engineering, Research, and Data Engineering teams to develop product features, evaluate business and product performance, guide product planning, and translate statistical findings into actionable recommendations. Manages and develops analytical talent while applying data storytelling, A/B testing, marketplace metrics, and retention, conversion, engagement, and churn analysis.

Develops, calibrates, validates, and maintains credit risk models, including PD, LGD, and EAD models, for lending, collections, loss forecasting, capital planning, and stress testing. Analyzes large datasets, evaluates model performance, documents model changes, supports systems testing, and communicates statistical insights to stakeholders and management. Collaborates across the credit union to improve risk-return strategies and reporting.

Leads Lyra Health’s AI/ML engineering roadmap, scales and mentors machine learning teams, and drives production-grade systems for clinical applications. Responsibilities include people leadership, quarterly planning, technical architecture, design reviews, model governance, ML SDLC oversight, and deployment of reliable microservices on Kubernetes. The role partners with product, data science, and clinical stakeholders while ensuring safety, operational excellence, cloud scalability, and compliance for sensitive healthcare data.

Leads complex enterprise SaaS delivery programs for major banks, owning governance, client and executive relationships, commercial controls, risk management, regulatory deadlines, third-party coordination, and successful go-live. The role requires deep financial crime compliance technology experience, including AML, KYC, transaction monitoring, sanctions screening, or case management platforms, plus proven Tier 1 bank implementations, program turnaround expertise, cloud delivery, and senior stakeholder credibility.

Lead independent validation and ongoing monitoring of complex financial and analytics models, including ALM, loss forecasting, loan transition, corporate finance, and engagement models. Identify weaknesses, communicate findings, guide remediation, and strengthen model governance. Collaborate with Finance, Quantitative Research, Growth Analytics, Internal Audit, Internal Controls, Accounting, and Compliance to maintain Affirm’s model risk framework and address audit, regulatory, and examiner requests.