Top Machine Learning Jobs in Kansas City, MO

Design, build, and deploy production-grade ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM applications, and scalable data pipelines with observability and MLOps practices for cloud and on-prem environments.

Design, build, and deploy production ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM features, data pipelines, observability, MLOps, and containerized deployments across cloud and on-prem environments.

The AI/Machine Learning Specialist designs and implements AI solutions, collaborates with cross-functional teams, and continuously improves ML processes.

Source, engage, and qualify technical candidates using LinkedIn, GitHub, X‑Ray, and other tools. Build pipelines for engineering and technical leadership roles, run outreach campaigns, perform initial screening, document candidate details in ATS/CRM, and partner with recruiters to meet client hiring timelines while improving sourcing strategies.

Lead vision, strategy, and execution for Alkami's marketing products. Define roadmap, embed AI-driven personalization and audience intelligence, partner cross-functionally to drive adoption and revenue, recruit and develop product managers, and deliver scalable SaaS marketing and analytics solutions for financial institutions.

Lead complex, cross-functional AI programs end-to-end: translate strategy into integrated plans, drive multi-team execution, mitigate risks (data, model, compliance), apply ML lifecycle practices, use Agile/kanban methods, manage budgets/vendors, communicate to senior stakeholders, and mentor other program managers to improve AI program standards.

Lead product analytics to improve user growth, engagement, retention, and revenue. Design and analyze A/B and multivariate experiments, perform funnel/cohort analyses, maintain KPIs and dashboards, ensure event tracking, leverage ML and AI tools for advanced analyses, and translate insights into product recommendations across cross-functional teams.

Design and lead end-to-end AI solution architectures, ensuring scalability, security, and compliance. Translate business and regulatory requirements into technical designs, evaluate tools/platforms, document architecture standards, coordinate technical teams, and support deployment and ongoing improvements.

Lead end-to-end data science and AI projects: translate business problems, prepare large datasets, build and deploy predictive/prescriptive and generative AI models (including LLM fine-tuning and prompt engineering), communicate insights to stakeholders, and promote responsible, explainable AI practices across consulting engagements.

Lead design, build, and operate an end-to-end Identity Platform for KYC/KYB, overseeing CIP, CDD, sanctions screening, and continuous risk monitoring. Drive AI-first automation to reduce manual reviews, mentor engineers, manage reliability and incidents, and represent technical solutions to customers and regulators. Partner cross-functionally to shape roadmap and ensure regulatory compliance and extensibility across jurisdictions.

Lead a team of safety engineers to define and execute AV safety strategy across development, simulation, testing, and deployment. Apply UL4600/ISO standards, develop safety cases, set safety metrics (SPI), manage safety plans and artifacts, train engineers, and coordinate with partners and stakeholders to validate ML models and ADS integration for safe public-road operation.

Lead design and scaling of a unified fraud and risk platform. Define product strategy, own fraud metrics, run SQL-driven analysis and A/B tests, and partner with engineers and data teams to build real-time detection, identity verification, and transaction monitoring. Balance customer experience with risk mitigation and communicate impact to executives, legal, and partners.

Design and implement machine learning models to solve business problems, analyze data for insights, and optimize model performance.

Lead technical pre-sales for large Oil, Gas & Energy accounts, define and implement Databricks-based data and ML/AI strategies, build technical champions, mentor teammates, and drive enterprise adoption through technical leadership and value selling.

Lead design, execution, and interpretation of A/B tests and quasi-experiments; apply causal inference methods; partner with product, engineering, and marketing; mentor data scientists; build experimentation frameworks; extract and analyze data using SQL and Python; communicate results to stakeholders.

Design, productionize, and deploy machine learning forecasting models for ad inventory and campaign performance in low-latency, real-time advertising environments. Build scalable simulation, budgeting, and pacing systems; collaborate with cross-functional teams to deploy models at scale and optimize ad monetization.

Lead research and experimentation to measure ad campaign performance and effectiveness. Design evaluation frameworks, build measurement solutions, develop models for lift, conversion, and attribution, run experiments and analyses, partner with product/engineering/design/sales, present insights, mentor teammates, and foster technical community and culture.

Lead integration of GenAI into game engines and production pipelines. Prototype AI-native gameplay with designers, optimize inference latency and memory to preserve framerate, build automation tools for asset and design workflows, mentor engineers, and translate research and open-source models into production-ready systems aligned with player experience.

Build and operate scalable, highly available ML/LLM serving and compute infrastructure. Own long-term platform vision, deliver zero-to-one projects, partner cross-functionally, optimize performance and capacity, and support production ML models at scale.

Lead design and execution of scalable experimentation frameworks for Netflix Ads. Develop auction-based, biddable media models, solve cold-start measurement problems globally, apply causal inference and ML, partner with product and engineering, and translate analytic results into strategic recommendations to optimize marketplace dynamics and member experience.

Lead design of Netflix's ads consumer experiences, building GenAI-powered pipelines, prototyping AI-driven ad formats, ensuring privacy/regulatory compliance, collaborating with product, engineering, and data science to scale personalized advertising across surfaces.

Lead large, cross-functional programs for Netflix Cloud Infrastructure and AI Platform. Shape multi-year strategy, drive migrations and platform adoption, structure ambiguous technical problems into executable plans, execute end-to-end delivery, manage dependencies and risks, influence investment and architecture, and enable ML practitioners to build, train, deploy, and operate models at scale.

Lead design, execution, and optimization of scaled lifecycle campaigns across email and in-product channels. Use marketing automation, behavioral data, and ML techniques to personalize journeys, drive activation, revenue, retention, and cross-sell. Analyze performance, generate insights, and collaborate with Growth, Product, Engineering, Data Science, Analytics, Sales, and Marketing stakeholders.

Lead and build a team that drafts and submits state-specific rating rules, underwriting guidelines, and forms; manage filing execution via SERFF, handle objection responses, coordinate cross-functional stakeholders, establish operating rhythms, improve documentation and controls, and coach staff to scale filing expertise and regulatory execution.

Early-to-mid career Product Manager to translate customer needs into product requirements for AI-driven scientific SaaS. Work cross-functionally with engineering, AI/ML, solutions, and commercial teams to prioritize backlog, run discovery, support launches, gather customer feedback, and define product metrics for customers in chemistry, manufacturing, and energy.