Top Senior Machine Learning Jobs in Kansas City, MO

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

Lead the development of innovative AI solutions, guide teams through complex challenges, and collaborate with diverse stakeholders to enhance operational effectiveness and achieve strategic objectives.

Manage AI engineering teams and client relationships, drive project deliverables, mentor staff, and uphold quality standards while leveraging advanced technologies.

The Senior Product Manager will oversee the strategy and development of telematics data products, manage cross-functional teams, and ensure product viability and market alignment through customer insights and technical fluency.

The Director of Product Management for ML Platform will own the product strategy and execution, mentor PMs, and collaborate with ML teams to enhance infrastructure and manage costs.

Lead teams building computer vision and machine learning for AI dash cameras, managing model lifecycle, coordinating with cross-functional teams, and driving AI product development.

As a Customer Success Engineer, you'll drive adoption and satisfaction for enterprise customers using Deepgram's voice AI technology, fostering strong relationships and aligning technical solutions with business objectives.

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.

Lead planning, deployment, tuning, and operational support of CrowdStrike Falcon's AI/ML detection and response capabilities. Implement and troubleshoot AI-driven detection models, automation playbooks, API integrations, and threat-hunting for customers. Provide training, mentorship, and customer-facing collateral while optimizing detection efficacy and integrating Falcon into customers' security workflows.

Manage a team of ML engineers to build and optimize Affirm's economic decisioning engine using advanced ML techniques. Collaborate across teams, provide technical leadership, and mentor engineers while driving a cohesive long-term ML strategy.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

The Enterprise Account Executive will manage the complete sales cycle, build relationships with senior leaders, and drive platform adoption within data-intensive organizations.

As a Staff Software Engineer, you will lead the development of computer vision systems for sidewalk inspection, overseeing model lifecycle, system architecture, and mentoring while improving deployment practices.

Lead the Forward Deployed AI Engineering team to build solutions, engage customers, and enhance cybersecurity with AI tools and data science.

The Senior Machine Learning Engineer will design, implement, and optimize machine learning models, drive AI initiatives, and collaborate cross-functionally to enhance SailPoint's AI capabilities.

Lead ML feature strategy and engineering for fraud detection, owning end-to-end pipelines, validating features at scale, and translating analytics into production ML systems. Drive tooling and architecture decisions, mentor junior team members, partner cross-functionally with product and risk teams, and apply practitioner-level ML knowledge to detect and prevent account takeover and scam activity.

Serve as primary post-sales strategic partner for largest enterprise clients, driving AI Agent adoption, ROI, optimization, governance, renewals, and cross-functional advocacy to turn customers into champions.

Lead and grow a team of 5-7 enterprise sales reps in the Bay Area, recruit and develop sales leaders, build business plans, drive new-logo acquisition and account expansion, manage the sales cycle from lead generation to close, develop GTM strategy, and report to the VP of Sales. Role supports ambitious quarterly and annual goals and may require occasional work outside standard hours.

Own marketing measurement, operations, and analytics: build and QA campaigns, set goals, measure performance and attribution, manage data infrastructure and segmentation, optimize lead scoring/routing, apply AI/ML for automation and predictive insights, and document scalable processes to drive demand generation and cross-team alignment.

Contribute to building and scaling ML development infrastructure for Copilot: design and optimize CI/CD for large-scale training, build developer tools, maintain multi-cloud infrastructure, and deploy/host models for inference and data generation while collaborating with cross-functional teams to improve reliability, performance, and model development workflows.

Lead customer-facing data science engagements: manage data acquisition and cleaning, build and evaluate scalable models, drive model best practices and ethics, write extensible code, research industry trends, define solution strategy, and collaborate across engineering and product teams to deliver AI/cloud solutions.

Lead statistical design and analysis for Phase I-IV clinical studies, develop protocols and SAPs, perform efficacy and exploratory analyses, run simulations, apply advanced methods (mixed models, longitudinal), oversee datasets (ADaM/CDISC), use R and SAS for analyses, and provide strategic statistical guidance to cross-functional teams supporting regulatory submissions.

Drive supply chain efficiency through data analytics, KPI development, process redesign, ERP/WMS/automation selection and implementation, Lean Six Sigma continuous improvement, AI-driven forecasting, cross-functional project leadership, audits, and change management with suppliers and 3PLs.

Design, build, and automate scalable batch and streaming data pipelines, implement data models and ETL, automate deployments, support ML/experimentation, maintain server architecture, and partner with stakeholders to deliver analytics and data-driven tools.