Top Senior Machine Learning Jobs in Oklahoma City, OK

Leads business architecture and requirements activities for a federal healthcare modernization portfolio. Facilitates stakeholder workshops, analyzes current and future-state processes, develops architecture artifacts and EDI documentation, translates business needs into functional and technical requirements, and supports data integration, migration, traceability, defect management, UAT, and process automation initiatives.

Architect and prototype scalable solutions for Twilio’s emerging technologies experimentation team. Lead AI, machine learning, and LLM-driven initiatives; guide technical direction; mentor engineers across the US and India; align prototypes with business goals; and ensure enterprise architecture, scalability, extensibility, and production readiness. The role requires extensive architecture or principal engineering experience, cloud expertise across AWS and Azure, full-stack development knowledge, database expertise, and strong technical leadership.

Owns the lifecycle of AI-powered analytics products supporting clinicians, from requirements and discovery through production and maintenance. Partners with data scientists, engineers, clinicians, and executives to define roadmaps, prioritize trade-offs, establish data contracts and SLAs, validate model results, track performance, and demonstrate ROI. Leads Agile scrum teams and drives cross-functional delivery in complex healthcare environments.

Own the AI product strategy and roadmap for HealthEdge’s HealthRules Payer platform. Identify and prioritize AI use cases across claims, member management, enrollment, benefits, and contracts; translate strategy into product requirements; and align product, engineering, data science, UX, marketing, and sales teams. Lead AI governance, regulatory compliance, customer presentations, go-to-market messaging, pilots, and feature commercialization while ensuring responsible AI use in healthcare payer workflows.

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

Own the design vision and execution for experimental AI-powered learning tools co-created with teachers and researchers. Design teacher- and student-facing products, create flows, wireframes, interaction designs, and functional prototypes, and facilitate collaboration across educators, researchers, engineers, and data scientists. Conduct usability testing and validate research hypotheses while navigating ambiguity, data-heavy workflows, and uncertain AI/ML-enabled features.

Leads enterprise manufacturing AI, machine learning, and Industry 4.0 initiatives across multiple plants. Develops and deploys solutions for predictive maintenance, process and quality optimization, energy efficiency, throughput, and OEE improvement. Establishes scalable data and AI platforms, governance, and MLOps standards while integrating industrial data sources. Leads and mentors data science teams, prioritizes projects, allocates resources, partners with cross-functional manufacturing stakeholders, and presents strategic recommendations and business cases to executives.

Manage paid social campaigns and full-funnel strategies across Meta, LinkedIn, TikTok, Pinterest, Snapchat, and other paid channels. Oversee client accounts, analyze performance, identify growth opportunities, build client relationships, and collaborate with SEO, creative, and analytics teams. Contribute to thought leadership, coach associates, maintain quality standards, and explore automation, AI, and LLM search visibility initiatives.

Own the strategy, execution, customer success, and go-to-market for Oscilar’s Device and Behavior product. Lead development of SDKs, signal pipelines, behavioral biometrics, agentic identity signals, data networks, foundation-model capabilities, and analyst experiences. Partner with sales and customers to drive adoption, shape product positioning, and deliver a device intelligence and digital identity platform for fraud, onboarding, authentication, and risk decisions.

Lead ecosystem-level data science and econometric analyses across Xbox, Game Pass, Console, PC, and Store experiences. Evaluate growth, engagement, monetization, experiments, incrementality, and investment ROI using statistical and causal inference methods. Build reusable analytical products and self-service capabilities, influence executive decisions, and mentor team members.

Supervise actuarial predictive modeling initiatives for insurance pricing, portfolio management, and planning. Collaborate with actuaries, data scientists, underwriters, and management to develop, validate, govern, and implement models. Establish assumptions, loss adjustments, usage guardrails, monitoring practices, and model documentation. Support regulatory filings, improve team workflows, contribute to strategic projects, and mentor staff in actuarial and technical skills.

Develop and maintain pricing and predictive models for credit insurance products. Analyze claims, loss ratios, portfolio performance, profitability, credit risk, and economic scenarios. Recommend pricing actions, support forecasting and reserves, evaluate underwriting strategies, and partner with underwriting, finance, claims, data science, and technology teams. Ensure model governance, documentation, and actuarial standards compliance.

Designs, builds, and operationalizes enterprise AI, generative AI, machine learning, and agentic AI solutions. Develops integrations, orchestration services, reusable tooling, deployment pipelines, monitoring, and governance controls. Partners with architecture, platform, data, and product teams to deliver scalable, secure, compliant AI capabilities across the organization.

Owns the strategy, roadmap, requirements, backlog, positioning, and lifecycle execution for proprietary software products. Partners with engineering, UX, QA, architecture, data operations, and project management teams in an Agile environment. Conducts market and competitive analysis, supports product launches, creates AI prototypes, develops client-facing content, and contributes to RFP responses. Requires strong technical, product leadership, communication, prioritization, and stakeholder-management skills.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

Lead and transform the Fraud Intelligence Team by designing scalable operating models, QA and measurement frameworks, and talent programs. Drive labeling quality, operational metrics, and fraud prevention impact; convert frontline fraud observations into insights for Product, R&D, Analytics, and GTM; leverage AI, automation, and tooling; and serve as a cross-functional fraud subject-matter expert while developing early-career talent and measurable business outcomes.

Build rigorous ROI analyses, value models, and business cases that translate AI ranking performance into revenue, margin, and cost-to-serve outcomes. Present analyses to CFOs, procurement teams, and other economic buyers; support sales pursuits; create reusable value-selling frameworks; tailor models to customer economics; and collaborate with product, data science, and customer teams to validate benchmarks and deployment results.

Own the full Global System Integrator partner lifecycle, including sourcing, agreements, joint go-to-market motions, enablement, delivery planning, and performance optimization. Build relationships across major GSIs such as Accenture, Deloitte, Bain, BCG, Slalom, and IBM. Collaborate with sales, product, and engineering teams to generate partner-sourced and influenced pipeline and revenue. Develop the GSI strategy, playbook, and operating processes for Sequen’s growing AI business.

Lead research and development of generative AI and recommendation solutions for Netflix promotional assets and content discovery. Responsibilities include tracking LLM research, developing summarization and LLM-as-judge systems, training and evaluating models, optimizing generated content for audience impact, partnering with engineering teams, defining ML roadmaps, and communicating technical strategies to stakeholders.

Architects and rapidly deploys AI agent systems, BI and ML pipelines, and data governance solutions for strategic enterprise customers. Acts as a technical bridge between customers, Product, Engineering, and GTM teams; develops reusable solution patterns and internal tooling; influences platform roadmaps and delivery methodologies; conducts competitive analysis; and mentors field and customer technical teams.

Develop complex healthcare reports, ETL solutions, databases, and Power BI dashboards for LTSS and Dual Eligible programs. Analyze multidimensional data, ensure governance and accuracy, identify operational improvements, and deliver actionable insights to leadership. The role translates business requirements into scalable reporting solutions, collaborates with clinical, operational, data engineering, and IT teams, and leads testing, process automation, visualization, and large cross-functional data projects.

Drive go-to-market reporting, business intelligence, forecasting, dashboard development, and ad hoc analysis. The role standardizes forecasting processes, maintains analytical documentation, automates reporting and data pipelines using AI-assisted tools, and delivers actionable insights to Sales, Marketing, Engineering, Finance, and executive stakeholders.

Build and lead the organization-wide adoption of generative AI, agentic systems, and AI-assisted development. Design production automation agents, evaluate coding tools, modernize rules-based workflows with ML, and establish responsible AI guardrails. Partner with engineering, product, data, and clinical teams to identify high-impact opportunities, own the enablement roadmap, measure outcomes, and drive adoption through working software, documentation, and hands-on collaboration.

Leads business analysis for AI and automation initiatives, identifying adoption opportunities, developing business cases, gathering requirements, and aligning business needs with technical solutions. The role facilitates stakeholder workshops, supports solution design, testing, deployment, change management, governance, and benefits realization. It also advises executives, monitors outcomes, promotes business analysis standards, and mentors junior analysts.

Leads operational oversight, performance analysis, governance, and continuous improvement for AI-powered products and services. Develops performance frameworks, executive dashboards, business insights, risk and compliance reporting, and scalable AI operating models. Partners with AI engineers, product teams, and business leaders to optimize workflows, support automation, manage operational risks, and drive cross-functional operational excellence.