Top Machine Learning Jobs in Kansas City, MO

Lead data engineering and machine learning initiatives by designing, architecting, developing, and supporting GCP data pipelines. Create information architecture documentation, estimate and plan technical work, collaborate with project teams and business analysts, and translate requirements into technical designs. Develop Python-based ELT pipelines, optimize BigQuery SQL, support CI/CD, and provide technical leadership to projects and teams.

Build analytical frameworks, measurement methodologies, and decision support to drive enterprise decisions across marketing, loyalty, pricing, menu, media, and operations. Mine and integrate customer, transaction, digital, and operational data; develop segmentation, predictive models, and dashboards; lead test-and-learn, incrementality, and forecasting efforts; translate analysis into clear business recommendations and scalable decisioning tools.

Leads the data science platform and machine learning strategy, building data marts, predictive models, MLOps infrastructure, and analytics capabilities. Analyzes healthcare claims, clinical, workflow, and operational data to risk-stratify patients, assess clinical program impact, support dashboards, and improve patient and provider engagement. Collaborates with clinical, operations, finance, product, executive, and technology teams while serving as a trusted analytics expert for a business workstream.

Develop deep learning and AI/ML models to predict cardiac events from ECG and physiological signals. Apply signal processing, analyze implantable-device datasets, build Python tools, validate algorithms, and support feasibility studies for diagnostic features. Collaborate with clinical, software, and hardware teams to improve implantable-device performance and patient outcomes.

Generates and qualifies leads through outbound outreach, manages sales pipelines and CRM activity, conducts product demonstrations, guides prospects through the sales process, builds customer relationships, meets quotas, and collaborates with marketing, product, and customer success teams. The role requires inside sales experience, SaaS or technology familiarity, strong communication and negotiation skills, CRM proficiency, and up to 20% travel.

Design and operate large-scale, AI-native cloud infrastructure (especially Kubernetes/AKS). Improve service quality, automate incident prevention/remediation, accelerate engineering productivity, and integrate AI tools into development workflows.

Delivers customer-facing training in AI, data, and software engineering; creates tailored courses, projects, certifications, and assessments on the DataCamp platform. Partners with Customer Success, Sales, Product, and Content teams to design blended learning paths, teach virtual and onsite sessions, tailor materials for varied audiences, and improve customer adoption, satisfaction, and measurable skills.

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.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Leads Clipboard’s Applied Science function and team, setting the science roadmap across marketplace pricing, auctions, causal models, metrics, and experimentation. The manager balances production modeling with analytical work, partners with engineering, product, finance, and operations, and mentors and hires scientists. Responsibilities include developing and deploying quantitative models, designing experiments, defining marketplace metrics, prioritizing initiatives, and communicating findings to business and technical stakeholders.

Leads the engineering team responsible for Airbnb’s globally scalable AirCover insurance platform. Sets technical strategy, architecture, roadmap, and operational standards for configurable insurance products, pricing, enrollment, coverage management, and experimentation. Partners with Product, Data Science, Legal, Insurance, Finance, and Operations to expand across regions and improve attach rates. Manages hiring, mentoring, career development, incident response, and engineering quality while guiding distributed, high-availability backend systems and ML-driven experimentation.

Leads advanced analytics initiatives supporting Tribal healthcare programs and strategic decision-making. Develops predictive and prescriptive models, integrates complex data sources, establishes data quality frameworks, evaluates healthcare data resources, and produces reports and dashboards. Coordinates cross-functional projects, ensures federal compliance, supports quality measurement, mentors junior staff, and may serve as a team lead.

Leads complex enterprise customer engagements as a technical authority for Databricks data and AI solutions. Drives architecture, platform adoption, consumption strategy, competitive positioning, and executive relationships. Designs large-scale data, streaming, migration, governance, and AI/ML solutions; orchestrates cross-functional teams; mentors other solutions architects; and contributes to technical thought leadership. Requires advanced coding, enterprise data architecture expertise, Databricks proficiency, strategic account leadership, and executive communication.

Leads large-scale enterprise application development, modernization, and sustainment programs. Oversees Agile teams, program governance, schedules, budgets, risks, resources, stakeholder communications, cloud modernization, DevSecOps, AI, user adoption, and cybersecurity compliance. The role coordinates technical and business stakeholders, manages Appian and Google Cloud initiatives, drives continuous improvement, and ensures delivery quality, security, performance, and alignment with government objectives.

Leads AI engineering strategy, team development, and delivery of scalable AI and machine learning solutions. Provides technical guidance on solution design, MLOps, automation, DevSecOps, testing, and operational readiness. Partners with business, data, security, architecture, and technology stakeholders to translate requirements into secure, reliable capabilities. Oversees delivery risks, dependencies, quality, governance, responsible AI practices, and continuous improvement while communicating progress and outcomes to leadership.

Lead product-focused data science and machine learning initiatives, including exploratory analysis, production model development, evaluation frameworks, generative AI, graph-based machine learning, recommendation systems, and personalization. Collaborate with engineering, product, and business teams to deliver high-impact solutions, influence strategy, and communicate insights to technical and non-technical stakeholders. The hybrid role requires four days per week in the Greater Boston area.

Staff Backend Engineer responsible for building data and machine learning systems that provide competitive travel-market intelligence. The role involves setting technical strategy, designing APIs and backend architecture, prototyping solutions, partnering with product and ML engineers, conducting design and code reviews, driving engineering best practices, and mentoring junior engineers.

Freelance writers summarize recent machine learning research papers for The Batch, an AI newsletter reaching over two million professionals and students. Writers must understand machine learning technology, explain complex research clearly in an established format, and communicate effectively in English. The role is intended for graduate students and postdocs in machine learning, with negotiable freelance compensation.

The Corporate Controller will lead accounting operations, month-end close, financial reporting, audits, tax compliance, payment reconciliations, internal controls, treasury, and exit-readiness activities. The role manages accounting systems, automation initiatives, vendor relationships, and accounting team development while partnering with FP&A, Payments, HR, and senior leadership. The position requires strong U.S. GAAP expertise, including ASC 606, audit leadership, AP operations experience, and familiarity with SaaS, payments, or FinTech environments.

Senior legal executive leading institutional bank partnerships, complex commercial and program agreements, consumer lending regulatory strategy, data protection, intellectual property, and AI underwriting compliance. The role advises executive and cross-functional teams, manages bank due diligence and risk requirements, and translates legal and regulatory considerations into scalable business strategies.

Leads the creation and global scaling of an AI Data Operations practice. Responsibilities include defining service strategy, developing AI data and evaluation solutions, originating and closing client engagements, establishing quality and governance frameworks, building strategic partnerships, providing thought leadership, and enabling scalable managed-service delivery. The role combines AI expertise, consulting, sales, solution design, commercial leadership, and global operations.

Leads the Growth Algorithms data science team, setting strategy for acquisition, activation, retention, and reactivation. Oversees experimentation, causal inference, predictive modeling, personalization, CRM, paid media, and lifecycle initiatives. Partners across Product, Marketing, Engineering, Finance, Design, and Analytics to prioritize high-impact work, improve decision-making, guide production-quality systems, and develop a high-performing team of data scientists.

Provides statistical strategy and biostatistical oversight for pharmaceutical clinical trials, including protocols, SAPs, clinical study reports, regulatory documentation, analyses, randomization, and vendor deliverables. Develops innovative statistical methodologies and tools, supports clinical development programs, reviews data management documentation, and contributes to cross-functional standards and infrastructure initiatives.

Own Avon AI’s US go-to-market motion, including enterprise prospecting, discovery, demos, pilots, negotiations, forecasting, and closing deals with regulated organizations. Build demand through outbound campaigns, events, webinars, partners, and resellers. Develop the sales process, messaging, qualification framework, and playbook while helping recruit the future US sales and marketing team. Collaborate closely with founders and product teams, translating customer and market feedback into product direction.

Develops machine learning models and production data science pipelines to improve subscription conversion, content recommendations, user understanding, workflow automation, and product decisions. Leads analytical projects and experiments, applies statistical methods to web-scale data, and collaborates with data, product, growth, and engineering teams. The role also communicates complex findings to diverse audiences and helps foster a strong data science culture.