Top Machine Learning Jobs in Oklahoma City, OK

Owns a portfolio of Data-as-a-Service products end to end, including vision, roadmap, requirements, agile delivery, pricing, packaging, distribution, privacy compliance, and go-to-market execution. Partners with engineering, data science, legal, marketing, sales, and customer success to deliver data enrichment, identity, and audience products through APIs, clean rooms, marketplaces, integrations, and self-service channels. Uses launch metrics and customer insights to guide investment decisions.

Leads technology development for composite wind blade design, materials, manufacturing, tooling, and automation. Owns maturation from early research through production implementation, establishes technology roadmaps and stage-gate processes, and applies AI/ML to engineering and manufacturing challenges. Builds technical teams, manages budgets and partnerships, directs modeling and validation, supports production transitions, develops business cases, and protects intellectual property. The role collaborates globally with engineering, operations, quality, suppliers, customers, universities, and technology partners.

Own the end-to-end rebuild of Nextdoor’s consumer search experience, including query understanding, retrieval, ranking, result quality, organic and sponsored content blending, and monetization. Define search relevance metrics, partner with engineering, data science, ML, research, design, and marketing teams, and use A/B testing to improve engagement and revenue while protecting user experience.

Build analytical frameworks, measurement methodologies, and decision support to drive enterprise decisions across marketing, loyalty, pricing, menu, media, and operations. Mine and integrate customer, transaction, digital, and operational data; develop segmentation, predictive models, and dashboards; lead test-and-learn, incrementality, and forecasting efforts; translate analysis into clear business recommendations and scalable decisioning tools.

Build and lead scalable frontend products for Airbnb’s Community Support Engineering organization. Responsibilities include architecting web applications, developing reusable frontend components, designing supporting server-side APIs, implementing testing and experimentation, optimizing accessibility and performance, collaborating with product, design, machine learning, and generative AI teams, shaping technical direction, and mentoring junior engineers.

Own the platform powering Airbnb’s AI Assistant, including request routing, knowledge retrieval, capabilities, actions, and evaluation. Set product strategy, define resolution and quality standards, analyze production data, diagnose system failures, and guide engineering, data science, policy, and knowledge partners. Lead generative AI launches, safety and readiness reviews, LLM evaluation systems, calibration, and certification while aligning cross-functional teams and communicating decisions to executives.

The Vice President of Sales will own Fuel Cycle’s sales function, including go-to-market strategy, quota attainment, pipeline generation, enterprise deal execution, forecasting, board reporting, and sales team development. The role requires building a new-logo growth engine, coaching Challenger and SPICED methodologies, navigating complex buying committees, partnering cross-functionally, and selling AI-powered SaaS solutions to enterprise customers. Regular travel to prospects, clients, and company headquarters is expected.

Leads commercial, privacy, and product legal functions for a cloud technology company. Drafts and negotiates complex SaaS, partnership, reseller, and technology agreements; advises on global privacy, data protection, AI, intellectual property, and product development issues; develops contracting processes and playbooks; partners with cross-functional teams; and manages, mentors, and develops legal professionals.

Develops, calibrates, validates, and maintains credit risk models, including PD, LGD, and EAD models, for lending, collections, loss forecasting, capital planning, and stress testing. Analyzes large datasets, evaluates model performance, documents model changes, supports systems testing, and communicates statistical insights to stakeholders and management. Collaborates across the credit union to improve risk-return strategies and reporting.

Close $1M in net-new bookings by selling AI transformation to CEO-led buying committees. Generate outbound pipeline, co-sell initially with the founder, then independently close complex mid-market deals. Build a repeatable sales playbook covering ICP, discovery, multi-threading, pricing, objections, and close plans. Feed deal insights into company packaging and pricing, with a path to build and lead the future sales team.

Drive pricing analytics, margin optimization, competitive intelligence, and AI adoption across Commercial Management. Develop pricing models, predictive analytics, AI-assisted recommendations, dashboards, and executive reporting to improve profitability, forecasting, governance, and commercial decisions. Automate reporting and workflows, monitor competitor and deal intelligence, identify margin leakage and growth opportunities, and present actionable insights to senior leadership.

Lead design and implementation of high-throughput, low-latency programmatic bidding systems. Collaborate with ML engineers to deploy real-time inference, optimize distributed microservices, run experiments and quantitative analysis, and partner with product to ship scalable features. Foster operational excellence, mentor engineers, and continuously improve performance and reliability.

Lead enterprise AI security architecture, strategy, governance, and secure-by-design implementation across cloud, hybrid infrastructure, software, and AI/ML environments. Design security patterns for LLM hosting, agentic systems, vector databases, and inference endpoints; translate regulatory requirements into technical standards; review complex architectures; implement AI security guardrails and policy enforcement; advise engineering and product teams; and mentor teams while influencing senior stakeholders.

Own the product strategy, roadmap, team, customer relationships, and P&L for Teamworks’ Coaching, Player Personnel, Recruiting, and Intelligence portfolio. Lead AI strategy across sports markets, integrate acquired products, align engineering, design, data science, marketing, and sales, and convert proprietary sports data into AI-powered workflows. Represent the business with teams, leagues, and partners while driving multi-market growth and product execution.

Design, train, and evaluate advanced machine learning models for autonomous driving, simulation, and ML platforms. Lead small cross-functional engineering teams, establish data and experiment practices for petabyte-scale training, address long-tail model failures, and work with multimodal datasets exceeding 100TB. The role requires commercial robotics experience, mentoring capability, expertise in VLA or generative world models, Python/PyTorch, sensor processing, and potentially edge deployment.

Lead high-complexity data science initiatives improving search ranking, retrieval, relevance, and evaluation. Develop and deploy production machine-learning and NLP solutions, investigate LLM-based ranking features, optimize SQL queries, and work with sparse privacy-preserving data. Define strategies for ambiguous problems, guide other data scientists, collaborate with product teams, and own projects from scoping through production.

Leads the credit risk data science function across underwriting, fraud, loss forecasting, profitability, and portfolio analytics. Owns the model development roadmap and lifecycle, including development, deployment, monitoring, governance, validation, and regulatory readiness. Manages and mentors data science talent, establishes technical standards, partners with cross-functional teams, and translates business objectives into scalable analytical solutions. Guides responsible AI adoption and communicates model performance, risks, and recommendations to senior leadership.

The Associate Data Scientist partners with clinical and operational teams to prepare and transform data, develop predictive models, apply statistical and AI techniques, and create actionable insights. Responsibilities include feature engineering, model optimization, data visualization, dashboards, stakeholder presentations, risk management, and Agile collaboration to improve patient care, hospital operations, and organizational outcomes.

Leads Intermedia’s global accounting organization and financial reporting operations, including GAAP compliance, audits, tax, internal controls, revenue accounting, close processes, and business combinations. Partners with executive leadership on strategy, projections, growth initiatives, and operational improvement. Builds and mentors a high-performing global team while advancing technology-enabled automation and process efficiency across the CFO organization.

Leads technical sales and executive evangelism for Verint’s Open CCaaS and CX Automation platform. Acts as a trusted advisor to C-suite customers, articulating ROI, AI, data science, and platform capabilities. Partners with Product, Sales, Solutions, Services, Marketing, and Customer Success teams to drive adoption, expansion, thought leadership, and opportunity closure. Requires deep contact center operations experience, strong data architecture knowledge, executive communication skills, and extensive travel.

Provides strategic and technical leadership for Lilly’s eDiscovery program across the full EDRM lifecycle. Manages legal hold systems, data preservation and collection, processing, review, production, vendor relationships, workflows, and chain-of-custody requirements. Evaluates AI, machine learning, TAR/CAL, predictive coding, and analytics solutions while ensuring defensible legal processes. Partners with Legal, Privacy, Records Management, IT, Compliance, Cybersecurity, outside counsel, and business stakeholders, and mentors team members.

Lead research and engineering of production-grade LLM/GenAI systems for cybersecurity: design models and architectures, drive data labeling and evaluation, collaborate with product and engineering to deploy scalable solutions, mentor data scientists, set technical strategy, and advance AI safety, red-teaming, and applied ML innovations for detection and operational use.

Lead development and deployment of large-scale LLM and GenAI solutions for cybersecurity. Drive research strategy, model training, evaluation, safety/red-teaming, and cross-functional productization. Mentor data scientists, set technical standards, and represent the team through publications and thought leadership.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

As an ML Ops Infrastructure Engineer, you will design CI/CD pipelines for ML, maintain deployment systems, and implement monitoring while collaborating with research teams to ensure model quality and performance.