Top Senior Machine Learning Jobs in Oklahoma City, OK

Lead vision, strategy, and roadmap for pricing platforms, owning internal Rating Plan Manager and tooling to speed model deployment, improve workflow reliability and observability, enable self-service experimentation, and support regulatory/state-level pricing needs through cross-functional collaboration.

Lead the creation and optimization of machine learning algorithms, develop and refine production-grade models, and drive testing of innovative algorithms using historical data.

The Senior Product Manager will lead AI product strategy at CoinMarketCap, focusing on user needs and data analysis to drive product development.

The Senior Engineering Manager at Planet leads the engineering team, focusing on delivering products for Defense Intelligence. Responsibilities include mentoring engineers, refining processes, and collaborating across teams for effective deployment of technology.

Lead strategy, roadmap, and delivery for Tekmetric's SaaS product for auto repair shops. Own user research, AI/ML product initiatives, cross-functional alignment, go-to-market coordination, and measurement of business outcomes. Train internal teams and iterate on features from concept through launch and optimization.

Lead product strategy and execution for data and AI platforms, driving GenAI/LLM initiatives, cross-functional collaboration, responsible AI governance, experimentation (A/B testing), measurement of model impact, and mentoring product teams to embed scalable ML capabilities into clinical and member experiences.

Lead the development of deep learning models for email data, optimize models, design evaluation frameworks, integrate products, and mentor junior researchers.

Lead the development and implementation of machine learning solutions, managing a team to drive strategic decisions and innovative business outcomes.

Lead a consortium advancing AI-driven neurodegeneration research: set strategy, build partnerships, manage multidisciplinary executive team, oversee product development and deployment, secure funding, ensure ethical AI and scientific integrity, and scale the platform to broader biomedical domains.

Lead strategy and execution for MarketScan data products and delivery experiences. Define portfolio vision, prioritize data product innovation and operational excellence, drive cloud and AI enablement, ensure data quality/compliance, engage executives and customers, and build a high-performing product organization to grow adoption and revenue.

The Senior Software Engineer will design and optimize recommendation algorithms, maintain data pipelines, and improve personalized user experiences using machine learning techniques and backend engineering skills.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

As a Principal Software Engineer, you'll architect and code backend services and ML models, integrate them with Salesforce, and mentor junior engineers.

Design, implement, and scale ML-based solutions for search and advertising; define data collection, evaluation, and production serving strategies; analyze data to inform development; communicate cross-functionally; produce technical reports; and stay current with advances in LLMs, vision models, and generative AI.

Design, build, and scale backend systems and APIs for high-transaction consumer products. Collaborate with product, credit, compliance, support, and analytics teams. Contribute to code reviews, technical planning, security, and operational excellence. Mentor peers and promote engineering best practices.

Lead the development of generative AI tools for fashion, guiding ML engineers, and implementing innovative AI systems and workflows.

As a Senior Machine Learning Engineer, you will enhance diffusion models, conduct research, collaborate on system implementations, and communicate findings effectively.

The Senior Customer Success Manager drives revenue growth by ensuring customer satisfaction, building strong relationships, managing renewals, and promoting product solutions aligned with client goals.

Design and implement data-centric cybersecurity solutions: develop ML algorithms and automation for security tools; discover, parse, map, and transform legacy RMF artifacts into OSCAL; migrate and analyze security data; reproduce dashboards/workflows in eGRC; collaborate with Professional Services; produce migration assessments and reports.

Lead strategy and execution for AI-powered nutrition and coaching features. Define product roadmap, partner with engineering/data/design, run experiments and evaluations, ship 0-to-1 ML products, and ensure responsible AI practices and measurable user impact.

Lead product development for Socure's core fraud platform: build reusable services, APIs, and ML-powered features (graph, signals, model lifecycle). Drive prioritization, cross-functional delivery, KPI definition, customer discovery, and integration to improve detection accuracy and operational performance across fraud products.

Lead BI analytics and governance for client accounts: manage BI analysts, deliver dashboards and reports, oversee data mapping, modeling, quality, and platform initiatives (Power BI/Databricks), advise stakeholders, drive analytics roadmap, and apply advanced analytics and ML to optimize workplace and portfolio insights.

Lead and scale quantitative trading and liquidity strategies for NEAR Intents. Design game-theoretic models, build signal generation and execution systems, develop research and simulation infrastructure, translate research into production, monitor performance, and hire and mentor a quantitative research team while partnering with protocol and product teams.

Design, build, and operate production-grade AI systems using ML, LLMs, RAG, and agentic workflows. Define evaluation strategies, implement data/retrieval/orchestration layers, apply MLOps/LLMOps, and partner with stakeholders to prioritize, monitor, troubleshoot, and improve AI solutions balancing quality, latency, cost, reliability, and maintainability.

Lead the integration of AI and digital solutions in manufacturing processes, driving adoption and measurable impact on efficiency, quality, and performance.