Top Machine Learning Jobs in Kansas City, MO

Design, scale, and optimize ClickUp's search infrastructure using OpenSearch/Elasticsearch. Improve relevance, speed, and real-time indexing, build vector search capabilities, create evaluation frameworks, and collaborate with AI/backend/product teams to integrate and troubleshoot search at scale.

Lead payments analytics by building scalable reporting, causal inference and ML models, designing experiments, partnering with product/engineering/finance to optimize payment processing, reconciliation, and settlement, and translating results into executive recommendations to drive global payments improvements.

Manage full-cycle recruiting for technical and consulting roles with emphasis on AI talent. Partner with leaders to build sourcing strategies, pipelines, and candidate evaluation for LLMs, prompt engineering, ML, and AI governance roles. Maintain ATS data, report metrics, document recruiting best practices, and deliver strong candidate and hiring manager experiences.

Design and build backend systems and APIs for AI-driven products, ensuring scalability, reliability, and integration of ML models while collaborating with engineering and product teams.

The Senior Backend Data Engineer will extend data ingestion and processing pipelines, build APIs and backend services, and provide technical leadership.

As a Senior Data Scientist, you will identify business opportunities, build machine learning solutions, partner cross-functionally, and translate analyses into actionable insights.

The Data & Analytics team at Surescripts transforms healthcare data into actionable insights, collaborating with various stakeholders to support critical decisions across the healthcare ecosystem.

Lead Tekmetric's API product strategy and roadmap for the SaaS platform. Own API lifecycle (contracts, versioning, documentation), drive developer experience and adoption, identify integration opportunities, lead generative AI initiatives, perform user research and analytics-driven prioritization, collaborate across design/engineering/sales, train internal teams, and measure business impact.

The Senior Manager will oversee the fraud lifecycle, optimize detection strategies, conduct fraud reviews, collaborate with teams, and manage risk reporting.

The Principal Data Scientist will design, develop, and deploy machine learning models, innovating methodologies and collaborating across teams to enhance financial decision-making and risk management.

Lead a global manufacturing engineering organization to standardize processes, drive lean continuous improvement, deploy automation and Industry 4.0 solutions (cobots, ML), and ensure safety, traceability, and zero-defect customer quality across international sites.

Lead sales and deployment of custom AI/ML solutions, driving pipeline and revenue for allocated accounts. Collaborate with Field Sales, Product, Sales Engineering and AI teams to discover requirements, architect agentic AI solutions, write SOWs, negotiate commercial terms, and manage complex sales cycles to ensure customer adoption and measurable business outcomes.

One-year, full-time fellowship supporting design, delivery, and evaluation of interventions for smallholder farmers. Duties include research and analysis, pilot design, field implementation, M&E, and cross-team collaboration with heavy mentorship and rotating in-country placements.

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.

Support revenue cycle by performing coding reviews, claim scrubbing, and payer audit management to prevent denials and recoupments. Use Power BI, advanced Excel, and a machine-learning tool to detect trends, validate exceptions, and drive upstream/downstream interventions. Liaise with stakeholders, track payer audit performance, and deliver operational improvements and monthly scorecards to leadership. Remote role focused on mental/behavioral health revenue integrity.

Lead planning, execution, and optimization of cross-functional hardware and software projects for robot development, manufacturing, testing, upgrades, and deployments. Coordinate mechanical, electrical, embedded, systems, manufacturing, and operations teams, define scope and timelines, mitigate risks, implement process improvements, run sprints, and maintain project documentation and stakeholder communication.

Lead statistical activities for Phase I-IV clinical trials from protocol design through reporting. Represent statistics on cross-functional teams, oversee programmers/CROs, perform QC and inferential analyses using SAS/R, apply statistical, machine learning and deep learning methods for modeling/simulation, and mentor junior statisticians.

Lead Woolpert's partner marketing for the Google relationship: develop and execute joint go-to-market plans, run integrated campaigns, enable sales, create partner collateral, measure KPIs, and coach one specialist to drive co-selling and pipeline growth for Digital Innovations.

Design, prototype, and deploy production-ready AI products using ML and generative AI. Lead cross-functional teams, collaborate with stakeholders to solve workflow problems, build scalable prototypes and proofs-of-concept, and apply latest ML/GenAI research techniques.

Lead a product marketing team to define go-to-market strategy, positioning, messaging, and launch execution for a SaaS product portfolio. Partner with Product, Sales, and Marketing to build sales tools, training, KPAs, and scalable processes while mentoring and managing team performance to drive product adoption and pipeline growth.

Lead statistical activities for Phase I-IV clinical trials from protocol design through reporting. Provide statistical oversight, collaborate cross-functionally, supervise programmers/CROs, apply SAS/R and ML/DL methods for analyses and automation, and support regulatory, safety, and publication deliverables.

Lead design and implementation of scalable data science and ML solutions: acquire and ETL data from S3/Redshift/Spark, analyze data quality and trends, build and validate statistical and ML models (including NLP and neural networks), deploy production models, mentor junior scientists, and communicate results to stakeholders and executives.

Lead development of Vanta's business analytics function: build scalable product data assets, define measurement frameworks, use AI-assisted analytics, partner with cross-functional teams, and deliver executive-level recommendations to drive product and business decisions.

Lead and grow a global engineering team building endpoint visibility, prevention, and on-device ML across Windows, macOS, and Linux. Own roadmap and delivery, direct model development and telemetry, drive cross-platform protection parity, coordinate with product and partner teams, and represent the team externally through research and conferences.

Build and own end-to-end product features across React/TypeScript frontend, Ruby on Rails backend, relational databases, and GCP/AWS infrastructure. Partner with product, design, clinical, and operations teams to translate complex healthcare workflows into simple experiences. Improve reliability and performance, mentor engineers, raise engineering standards, and integrate AI-powered features into production.