Top Machine Learning Jobs in Kansas City, MO

The role involves leading ML client engagements, shaping strategies, advising on ML architecture, and influencing project outcomes, while guiding teams and driving business value.

The role involves designing, training, and evaluating ML models, optimizing performance, and collaborating with teams to implement AI technologies in products.

The Senior Machine Learning Engineer at Grailed will enhance personalization and recommendations, develop AI/ML solutions, and collaborate across departments for data-driven insights.

Build and maintain MLOps pipelines, deploy and monitor ML models as scalable services, transform and integrate healthcare data (FHIR/HL7), ensure reproducible feature management, and uphold HIPAA/HITRUST security for production ML in clinical systems.

As an AI/ML Presales Solutions Architect, you will engage with clients to identify problems, create feasible AI solutions, and partner with sales to ensure project delivery aligns with capabilities. You will leverage your extensive experience in AI and cloud platforms to shape presentations and technical discussions with clients.

Design, build and deploy production AI/ML solutions from complex, distributed farm data. Engineer features, select models, run experiments, move models to scalable real-time production, monitor and observe AI systems, evaluate emerging AI technologies, and collaborate with product, engineering and domain teams. Contribute to user-facing features with React/TypeScript as needed.

Design, build, and deploy production-grade AI/ML solutions that convert complex, distributed farm data into actionable intelligence. Engineer features, select models, run experiments, and move models to scalable, real-time production. Integrate, fine-tune, monitor, and observe models on cloud infrastructure (AWS, Databricks). Partner with product, engineering and domain teams and contribute to user-facing experiences when needed.

Summer internship working on transformer-based models to automate scoring of Spanish constructed responses. Collaborate with psychometricians and data scientists to design experiments, implement models in Python, evaluate with industry metrics (QWK, accuracy, SMD), and document and present findings.

Design, prototype, and ship LLM- and agent-powered AI features for observability. Rapidly iterate with real users, integrate AI workflows with tooling and alerting, collaborate cross-functionally, and ensure scalable, production-ready solutions in cloud-native environments.

Evaluate and strengthen AI model behavior on cybersecurity topics by writing expert prompts, annotating and grading model responses for accuracy and safety, and applying structured guidelines to classify sensitive content. Work part-time on AI safety tasks with emphasis on secure, responsible handling of dual-use information.

Own growth and performance for Kits AI across funnel optimization, activation, retention, pricing, and monetization. Productize ML capabilities into creator-facing workflows, partner with research and engineering, run experiments and analytics (e.g., Amplitude), conduct customer research, and leverage AI tools to accelerate shipping and internal insight systems.

As a Senior Impact Analyst, you will analyze sustainability challenges, design and manage interventions, and work closely with smallholder communities, emphasizing rigorous research and collaboration.

Lead design, development, and production deployment of ML and generative AI solutions at scale. Drive personalization, pricing, experimentation, agentic AI, and simulation modeling. Partner with engineering and product teams, mentor engineers, influence technical strategy, and measure business impact through data-driven experimentation.

Lead architecture and implementation of large-scale generative, agentic, recommendation, and personalization ML systems. Build end-to-end ML platforms (data pipelines, training, deployment, monitoring, governance), define technical strategy and reusable patterns, and partner with Product, Engineering, Data, and Design to deliver production AI experiences for millions of customers.

Design, develop, and deploy machine learning models and scalable MLOps pipelines. Collaborate with data engineers and product teams to build, monitor, and optimize production ML systems, document experiments, and identify ML opportunities.

Design, build, and operate ML infrastructure for training, evaluation, deployment, and inference. Improve reliability, scalability, latency, throughput, and cost. Create pipelines, observability, benchmarking, and tooling to enable fast experimentation and productionization of models while diagnosing regressions and bottlenecks.

Design, evaluate, and productionize generative AI/ML solutions (RAG, agents, embeddings, retrieval). Build evaluation frameworks for hallucination detection, benchmark LLMs, optimize prompts/models, create datasets, fine-tune models, and collaborate to deploy and monitor enterprise-scale GenAI systems.

Build and maintain backend and full-stack marketplace features while supporting ML Ops infrastructure (model deployment, feature stores, real-time pipelines, monitoring). Collaborate with data scientists to bring models to production, write well-tested code, address performance and scalability issues, and contribute to technical planning and cross-functional communication.

Build and maintain full-stack marketplace features and support ML Ops infrastructure (model deployment, feature stores, real-time pipelines, monitoring) on Chalk and Vertex AI. Collaborate with data scientists to productionize models, write well-tested code, address performance/scalability issues, and contribute to technical planning.

Lead development of scalable AI/ML capabilities for Mail Intelligence: build LLM- and ML-based personalization, data pipelines, tools, and observability. Mentor engineers, collaborate cross-functionally, run A/B tests, implement feedback loops, and balance cost/quality/speed tradeoffs to deliver production-grade solutions.

Design, build, and deploy scalable distributed deep learning pipelines and infrastructure. Optimize hardware utilization, profile and benchmark training, manage large datasets, and enable reproducible ML workflows in cloud environments. Collaborate with ML scientists and engineers to align pipelines with research goals and drive performance, reliability, and operational best practices for large-scale model development.

Paid 3-month remote contract for students or recent grads to build and test LLM-based solutions using the Token Factory inference platform. Assist senior SAs with prompt engineering, model selection, benchmarking, and inference optimization. Run performance and quality experiments and contribute to internal tooling and automation. Mentorship provided; strong performers may be considered for full-time roles.

Seeking a Senior Full Stack .NET Developer to work on a social good project, with strong skills in C#, AngularJS, design, and UX. Requires 5+ years of experience.

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

Lead manufacturing process improvements for precision optical production: analyze data, reduce cycle time and costs, design/qualify tooling and automation, apply Lean/Six Sigma and AI-enabled analytics, maintain process documentation, partner cross-functionally, drive CAPEX and continuous improvement projects, and train production staff.