Top Senior Machine Learning Jobs in St. Louis, MO

Leads pricing strategy and profitability consulting engagements, analyzing pricing models, customer value, market trends, and business performance. Directs teams, manages stakeholders, budgets, and resources, and coaches consultants. Applies predictive analytics, machine learning, statistical modeling, and scenario analysis to develop actionable recommendations, improve client profitability, optimize customer value, and support strategic transformations.

Performs imagery and geospatial intelligence analysis supporting NGA and machine learning training data. Creates, reviews, verifies, annotates, and categorizes imagery and multi-INT data; applies photointerpretation, targeting, precision mensuration, GIS, and order-of-battle expertise. Trains and mentors junior analysts while collaborating across teams. Uses imagery exploitation and GIS software, geodatabases, and potentially Python scripting to produce intelligence products and support AI platforms.

Develop and implement AI solutions and machine learning systems that enhance products and solve complex client problems. Responsibilities include advanced analytics, LLM production deployment, prompt engineering, RAG pipeline optimization, cross-functional collaboration, technical discovery, responsible AI advocacy, client relationship building, and mentoring junior team members.

Leads pricing and revenue data science initiatives for consumer markets clients. Develops predictive models, forecasts trends and customer behavior, manages dashboards and visualizations, ensures data quality, and translates complex analytics into strategic decisions. Oversees client engagements, validates outcomes, directs complex projects, and coaches diverse, high-performing teams.

Lead go-to-market strategy for Sprout Social’s AI portfolio, including the Trellis AI agent. Develop enterprise launch playbooks, positioning, executive messaging, campaigns, and enablement programs. Analyze market and competitive dynamics, influence product roadmaps, improve launch processes, and partner with Product, Sales, Revenue, Brand, and executive leadership to drive adoption, revenue growth, deal expansion, and category leadership. The role also mentors marketing team members and operates with substantial autonomy.

Lead agile design and development projects for mobile apps and digital products. Coordinate product, design, engineering, marketing, leadership, and client stakeholders; manage project plans, scope, requirements, backlogs, acceptance criteria, deadlines, workflows, and deliverables. Support scoping and client relationship management while ensuring successful end-to-end software launches and alignment with business objectives.

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.

Develop and operate production ML and AI systems powering patient experiences such as matching, ranking, recommendations, onboarding, and personalization. Build reusable ML infrastructure, pipelines, evaluation, observability, and model-serving capabilities. Provide technical leadership across the ML lifecycle, guide architecture, evaluate custom versus foundation-model approaches, and partner with ML and Patient Engineering teams to deliver reliable, scalable AI products.

Leads the AI Engineering team across applied AI features and foundational ML infrastructure. Responsibilities include managing Senior and Staff engineers, hiring and coaching, deploying LLM-powered capabilities, building MLOps and AI observability platforms, balancing product delivery with platform investment, and ensuring privacy, compliance, evaluation rigor, and clinical safety in production systems.

Own the strategic vision and roadmap for Coursera’s AI-driven search experience. Lead conversational search, personalization, semantic and multilingual search, ranking, and discovery improvements. Partner with engineering, design, research, data science, ML, marketing, and partnerships teams to deliver scalable platform capabilities. Use experimentation, market analysis, KPIs, and customer insights to improve conversion, merchandising, learner experience, and revenue.

Set the technical vision for data science, lead complex statistical and machine learning model development from concept through production, and architect scalable modeling platforms and pipelines. Develop credit risk, pricing, and loss forecasting models; establish model governance standards; partner with senior leaders; mentor data scientists; and communicate technical strategy to executives. The role emphasizes production deployment, monitoring, cloud architecture, and high-impact decision-making across the business.

Develop and maintain production machine learning models, build scalable training and serving technologies, optimize real-time and batch ML pipelines, and monitor model performance and drift. The role involves deep neural networks, recommendation systems, automated retraining, ML research, engineering excellence, and communicating technical concepts to diverse audiences. Candidates need 6+ years of industry ML experience, strong coding skills, and experience deploying neural networks at scale.

Design, build, deploy, and support scalable Java microservices on AWS. Provide technical leadership, architectural direction, code reviews, troubleshooting, proof-of-concept development, and cross-functional collaboration. Work with high-throughput data, messaging systems, distributed architectures, observability, and AI-assisted development tools. Participate in on-call support, mentor engineers, lead architectural initiatives, and deliver reliable SaaS platform features.

Product Counsel will advise product, engineering, data science, marketing, compliance, and sales teams throughout the product lifecycle. Responsibilities include counseling on regulatory compliance, privacy, intellectual property, consumer protection, AI and machine learning, data rights, platform architecture, APIs, identity and account security, and marketing. The role translates legal requirements into technical guidance, supports AI governance, monitors evolving laws, and develops scalable legal processes for a fast-paced technology company.

Lead GitLab’s company-wide strategy for autonomous, agentic software development workflows. Identify and validate AI opportunities across the SDLC, build prototypes and reference architectures, establish evaluation frameworks and safety controls, and drive internal adoption. Partner across Engineering, Product, Infrastructure, Security, Architecture, and Data and ML teams to scale reliable, observable, compliant agentic capabilities into customer-facing products. Mentor senior technical leaders and represent GitLab externally on AI-assisted development and productivity measurement.

Supports payer modernization and health services consulting engagements by analyzing operational challenges, optimizing processes, applying business analytics, engaging stakeholders, implementing quality standards, and guiding transformation initiatives. Develops operational support frameworks, conducts market research, manages change, and advises clients on improving service delivery and business performance while mentoring junior team members.

Leads technical customer engagements for strategic enterprise accounts, combining solution engineering, software implementation, consulting, and sales support. Responsibilities include discovering requirements, designing and documenting SailPoint solutions, conducting foundational implementations and proof-of-value engagements, educating customers on architecture and best practices, and developing AI-enabled demonstrations and agentic solutions. The role collaborates across sales, product, professional services, partners, and customer success, and may require up to 15% travel.

Build and operate production machine learning systems for Safety AI, including low-latency APIs, data pipelines, model serving, evaluation, monitoring, and rollout infrastructure. Process large-scale camera and telematics data, optimize cloud and edge-to-cloud execution, track model performance and drift, and partner with applied scientists, firmware engineers, platform teams, and product managers to deliver reliable safety features.

Engineer AI-powered threat detections, automated response playbooks, and continuous adversary emulation. Apply machine learning and LLMs to security operations, conduct threat hunting and AI red teaming, map coverage to MITRE ATT&CK, and develop detection-as-code through CI/CD. Build production-grade Python integrations, measurable containment capabilities, and safe autonomous defenses with guardrails. Mentor security professionals and collaborate across threat response, cyber defense engineering, and platform teams.

Design, build, and operate high-throughput, low-latency ad-serving infrastructure processing millions of requests per second. Optimize GPU-powered TensorRT inference, feature stores, model serving, benchmarking, experimentation tooling, and system reliability. Partner with machine learning engineers to productionize models and own systems through design, deployment, observability, capacity planning, incident response, and optimization.

Owns P&L performance, profitability, growth, and digital transformation for Small and Lower Mid-Market commercial insurance portfolios. Leads pricing, underwriting, portfolio monitoring, analytics, data visualization, predictive modeling, and machine learning initiatives. Partners with actuarial, product, engineering, technology, and distribution teams to implement process improvements and underwriting actions across digital channels and geographies. Communicates insights to stakeholders and senior leadership while leading cross-functional teams in an Agile operating model.

Leads AI- and data-driven manufacturing transformation strategies for Life Sciences clients. Advises C-suite and operations leaders, develops AI strategies, business cases, roadmaps, operating models, and responsible AI plans, and oversees large-scale greenfield and brownfield manufacturing programs. Drives digital twin, automation, data platform, advanced analytics, generative AI, and AI/ML deployments from proof of concept through enterprise scale. Builds executive relationships, originates opportunities, manages partner ecosystems, develops manufacturing capabilities, and leads teams, delivery, financial performance, and risk.

Leads geospatial research using remote sensing, GeoAI, machine learning, image processing, and multi-source satellite and drone data. Responsibilities include designing experiments, conducting field surveys, analyzing geospatial datasets, developing grant proposals, publishing findings, coordinating interdisciplinary projects, and guiding team members. Research areas include environmental monitoring, greenhouse gas emissions, precision agriculture, food and water security, and climate-related land-use studies.

Build and productionize traditional machine learning models, owning feature engineering, validation, deployment, monitoring, drift detection, and retraining. Develop LLM-powered agentic tools, dashboards, self-serve analytics products, and automated insight pipelines. Partner with engineering and business stakeholders, write production-grade Python and SQL, drive adoption, improve data quality, and establish responsible AI workflows for a regulated industry.

Leads Emerson’s global supply chain analytics and digital transformation initiatives. Owns reporting, business intelligence, data quality, governance, systems optimization, automation, and advanced analytics solutions. Manages analytics professionals, partners cross-functionally with Supply Chain, IT, Logistics, and business units, and communicates actionable insights to leadership. The role also develops training, drives standardized tool adoption, and advances predictive modeling and data-driven decision-making.