Top Remote Machine Learning Jobs in Oklahoma City, OK

The Senior Machine Learning Engineer will utilize deep experience and insights to enhance communication and digital interactions through advanced machine learning tools and algorithms, focusing on unstructured data.

The Director of Data Sciences leads a team in strategic initiatives, drives machine learning and AI solutions, and manages resources to enhance data-driven decision making across the business unit.

Design, build, and automate scalable batch and streaming data pipelines, implement data models and ETL, automate deployments, support ML/experimentation, maintain server architecture, and partner with stakeholders to deliver analytics and data-driven tools.

Lead and own cross-organizational technical programs for ML and robotics platform development, define roadmaps and milestones, remove blockers, align diverse engineering teams, and drive adoption of platform best practices to deliver scalable autonomy and infrastructure outcomes.

The Staff Machine Learning Engineer will lead ML systems development for personalization and ranking, design architectures, and mentor team members, ensuring reliable operations at scale.

The Technical Product Marketing Manager will drive product marketing strategy, understand Socure's technology, craft technical narratives, and enhance internal and external communication through enablement materials.

The Data Scientist will build machine learning models to enhance claim audits, optimize performance, and improve healthcare decision-making by analyzing complex data sets.

The Director will lead Macmillan's corporate social media and community growth strategy, enhancing engagement and driving measurable growth across digital platforms through strategic content and analytics.

The Global Head of Solutions Engineering leads a team, ensuring technical excellence and customer success in pre-sales and onboarding while driving team development and cross-functional partnerships.

The Director of Product Management will lead a team to manage CAMP's Aircraft Health Management platform, driving product strategy, modernization, and execution with a focus on customer outcomes and market innovation.

The Cloud Inference Engineer is responsible for building and maintaining a scalable LLM inference platform, focusing on distributed systems and machine learning technologies while collaborating across teams to optimize performance.

You will execute and improve insurance workflows, analyze operational efficiency, collaborate with product teams, and support onboarding and documentation efforts.

Work on-site with portfolio companies to design, prototype, and deliver full-stack digital and AI solutions. Lead discovery, deployment, and post-launch iteration, ensure security/compliance, resolve technical issues, mentor teams, and drive enterprise integrations and adoption. Frequent domestic travel and stakeholder management required.

The Junior-Midlevel Developer will build and enhance Dumroo.ai's AI-powered education platform, collaborating on software components, data pipelines, and machine learning features.

Lead enterprise sales for Hippocratic AI to commercial-stage biotech accounts. Manage end-to-end deals, build ROI business cases, maintain pipeline and forecasting, partner with Product/Clinical/ML teams, and represent the company at industry events to drive growth and large strategic contracts.

Lead marketing analytics and root-cause investigations across the B2B SaaS funnel. Maintain data integrity and dashboards, monitor integrations (Marketo, Salesforce, 6Sense, Snowflake), quantify impact of trends, and recommend corrective actions. Architect and train AI/agent-driven analytics (Ask Anything), build semantic layers in Sigma/Snowflake, validate agent outputs, and partner with Revenue Marketing and Strategy teams to drive data-backed decisions and mentor junior analysts.

The Staff Data Scientist will lead the development and deployment of ML and GenAI systems to detect billing errors and fraud in healthcare payments, collaborating with cross-functional teams.

The Senior Manager of Data Insights will lead a team to optimize data sharing and governance, develop data strategies, and deliver actionable business intelligence across Docker's operations.

The DS&ML Group Product Manager oversees Data Science and Machine Learning capabilities, defining strategic vision, managing product portfolios, and ensuring delivery aligned with business needs. Responsibilities include developing roadmaps, executing models, scaling functionalities, and mentoring a team.

The role involves leading strategic AI partnerships, driving revenue growth, and managing cross-functional teams while advocating for AI initiatives internally and externally.

As a Senior Staff Machine Learning Engineer, you will drive AI product development, collaborate with cross-functional teams, and enhance ML models at scale.

Lead technical pre-sales engagements, design tailored solutions, demonstrate platform capabilities, assess customer needs, and expand relationships within life sciences and health technology.

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.

Design, build, and deploy novel sensor hardware and data acquisition systems; curate geoscientific datasets; develop statistical, physics-based, and ML models (2D/3D) to predict mineralization; create visualizations and evaluation tools; collaborate with geoscientists, engineers, and vendors; deploy sensors in the field and integrate results to guide exploration programs.

Lead operational excellence for enterprise AI/ML platforms: ensure reliability, scalability, observability, governance, and deployment readiness. Build automation, CI/CD, IaC, monitoring, and model lifecycle processes. Serve as senior escalation for incidents, drive root cause analysis, mentor engineers, and partner across Data, Infrastructure, Security, and Product teams to enable production AI workloads and generative AI adoption.