Top Senior Machine Learning Jobs in Oklahoma City, OK

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Lead teams applying advanced data science and machine learning to large-scale claims, clinical, and member data to generate actionable insights that reduce cost of care and improve population health. Manage client relationships, mentor staff, ensure project delivery and quality, develop payer-focused analytics products, present findings to senior stakeholders, and promote continuous improvement and knowledge sharing.

Lead Amazon performance marketing strategy and execution, manage Sponsored Ads and DSP, collaborate with agencies and cross-functional teams, optimize campaigns and budgets, analyze performance with AMC/analytics, and measure commercial impact to drive ROAS and customer acquisition.

Lead corporate communications strategy and execution: own product and model launches, media and executive communications, narratives, social presence, and major company moments. Translate technical research and product advances into compelling stories for developers, enterprise buyers, partners, and analysts. Partner cross-functionally with CEO, CMO, product, brand, and demand gen to build credibility and influence in the voice AI ecosystem.

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.

Leads Toast’s AI and analytics strategy for Enterprise Care. Owns the roadmap, evaluates and deploys AI-assisted support tools, develops operational intelligence products, and partners with Product, Engineering, and Data teams to move pilots into production. Establishes complexity and workload intelligence, assesses AI readiness, translates AI performance into measurable operational outcomes, and builds organizational AI literacy. The role requires extensive enterprise support or service-delivery leadership, hands-on production AI experience, operational data fluency, and the ability to drive trusted adoption among agents and executives.

Lead end-to-end delivery of AI and ML services within Managed Services. Manage project planning, budgeting, execution, and quality. Mentor and develop team members, cultivate client relationships, implement model monitoring and operationalization practices, and collaborate with architects and engineers to ensure compliant, reusable AI solutions.

Lead CrowdStrike Finance & Accounting AI transformation: define operating model and governance, prioritize AI use cases, oversee POC-to-production delivery, drive enablement and change management, measure benefits realization, and report outcomes to executives.

Leads technical pre-sales and foundational implementation engagements for SailPoint SaaS solutions. Discovers customer requirements, maps them to product capabilities, delivers proof-of-value implementations, explains architecture and best practices, and collaborates with sales, product, services, and customer success teams. Develops AI and agentic technology solutions for demonstrations and customer problems, while serving as a technical and consultative advisor to customers, partners, and colleagues.

Lead technical customer engagements for strategic accounts, supporting sales, solution design, foundational implementations, and proof-of-value deployments. Discover requirements, map them to SailPoint solutions, educate customers on architecture and best practices, collaborate across sales, product, professional services, and customer success, and develop AI- and agentic-technology solutions for demonstrations and customer outcomes.

Supports enterprise sales by discovering customer requirements, mapping them to SailPoint solutions, and delivering foundational implementations and proof-of-value engagements. Acts as a technical lead and consultative advisor, educating customers on architecture and best practices. Collaborates with sales, product, professional services, partners, and customer success teams while developing AI-driven and agentic solutions for demonstrations and customer outcomes.

Forward Deployed Engineers support sales and customer engagements by discovering requirements, designing and implementing foundational SaaS solutions, delivering proof-of-value implementations, and educating customers on architecture and best practices. They collaborate with sales, product, professional services, and customer success teams; use AI and agentic technologies to solve customer problems; lead technical engagements; document requirements; and develop reusable demonstration solutions. The role may require up to 15% travel.

Forward Deployed Engineers support enterprise sales and customer engagements by discovering requirements, mapping them to SailPoint solutions, and delivering foundational implementations and proof-of-value projects. They provide technical leadership, explain architecture and best practices, collaborate across sales, product, services, and customer success teams, and develop AI- and agentic-technology solutions for demonstrations and customer problems. The role requires strong client communication, software implementation expertise, SaaS architecture knowledge, and familiarity with enterprise infrastructure and identity governance.

Leads a data science team focused on customer intelligence and personalization across digital products, apps, newsletters, and marketing channels. Develops lifetime value, segmentation, retention, recommendation, attribution, forecasting, and engagement models. Owns product funnel analytics and experimentation, including A/B testing and causal inference. Partners with Product, Marketing, Editorial, Data Operations, and Engineering to translate customer behavior into product improvements, measurable growth, and scalable data capabilities.

Analyze and characterize conversational audio data, identify underrepresented areas, and build active-learning and human-in-the-loop workflows. Develop representative benchmarks, automate model adaptation, and create reusable data analysis and scoring systems. Partner with research, engineering, and data teams to run experiments, improve models, organize data, and translate complex findings into measurable product improvements.

Leads enterprise business and technology architecture for AI, platforms, integrations, and shared services across Corporate and Institutional Banking. Defines target-state architecture, standards, reference architectures, governance, and modernization strategies. Partners with business, engineering, data, security, and product teams to enable cloud-native platforms, APIs, event-driven systems, microservices, and reusable services. Manages business architects, coordinates technology and business initiatives, influences senior stakeholders, and drives scalable, secure, resilient architecture aligned with financial-services requirements.

Lead the In-Vehicle Experience team at Samsara, focusing on transforming in-cab cameras into intelligent companions. Collaborate with engineering, prioritize features, and ensure client interactions highlight trust and connection. Conduct customer research and integrate AI and ML into product features.

Lead independent validation and ongoing monitoring of complex financial and analytics models, including ALM, loss forecasting, loan transition, corporate finance, and engagement models. Identify weaknesses, communicate findings, guide remediation, and strengthen model governance. Collaborate with Finance, Quantitative Research, Growth Analytics, Internal Audit, Internal Controls, Accounting, and Compliance to maintain Affirm’s model risk framework and address audit, regulatory, and examiner requests.

Lead deployment, configuration, optimization, and operational support of CrowdStrike Falcon AI/ML detection and response capabilities. Tune ML models, build automation playbooks, develop scripts using Falcon APIs, integrate AI features with customer toolchains, support incident response and threat hunting, deliver customer workshops, and mentor team members. Travel up to 25%.

Partner with healthcare clients to design, prototype, and deploy production-grade AI/LLM solutions. Lead discovery, architecture, cloud integration, and delivery while troubleshooting distributed systems and driving measurable client outcomes.

Lead scientific and strategic AI efforts for Vaccines Medical: define AI vision and roadmap, govern responsible AI standards, prioritize and deliver validated AI-enabled solutions, partner cross-functionally, oversee deployment and adoption, manage budget and vendors, and ensure regulatory, ethical, and scientific compliance across global medical affairs.

Lead and architect high-value healthcare analytics engagements, build reusable analytic frameworks (DBT), partner with product and engineering, mentor analysts, ensure analytic quality, and represent Arcadia externally to drive population health and value-based care outcomes.

Own Secret Detection and Vulnerability Research as a product: define strategy across prevention, detection, validation, revocation, and reporting; ship detection content and intelligence with measurable quality; drive adoption, retention, and revenue; partner with engineering, research, and Field; use AI to accelerate research and productization.

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.

Lead design, build, and deploy scalable, reliable Java-based microservices in a cloud-native, event-driven AWS environment. Own backend feature design, code quality, automated testing, and FedRAMP release processes. Mentor engineers, participate in on-call/TechOps, integrate AI tools into development, and drive architecture, observability, and cross-team initiatives.