Top Machine Learning Jobs in Fayetteville, AR

The R&D Engineer will build and refine software solutions for defense use cases, prototype systems, and convert stakeholder feedback into technical requirements. Collaboration with engineering teams and customer-oriented engagements are key responsibilities.

As a Staff Machine Learning Engineer - AI Tech Lead, you will lead the design of AI systems for security operations, focusing on scalable architectures, AI safety, and mentoring. Responsibilities include overseeing technical evaluations, production workflows, LLM fine-tuning, and collaboration with teams to enhance AI capabilities.

As a Machine Learning Engineer, you will fine-tune transformer models, deploy machine learning solutions, and work with cross-functional teams on innovative projects.

The job involves building responsive web dashboards, advanced data visualizations, and analytics tools for unmanned aircraft systems, requiring a deep understanding of UI/UX design and data presentation.

Design, build, and deploy machine learning models for a payments platform, overseeing end-to-end solutions and experimentation, while monitoring models in production.

The Machine Learning Engineer will develop AI/ML solutions on AWS, optimize data pipelines, and support cloud migration projects while collaborating with stakeholders.

Manage AI/ML projects from Proof of Concept to Minimum Viable Product using Agile methodologies while ensuring stakeholder communication and project alignment.

Design, build, and operate production-grade ML systems for personalization, search, and recommendations. Own end-to-end pipelines from data ingestion and modeling to deployment, monitoring, and iteration, ensuring scalable, reliable, and observable services.

Design and maintain datasets, build and evaluate domain-specific ML and vision-language models for real-time privileged access threat detection; deploy and optimize Python/Docker inference services integrated with WebSocket/WebRTC and protocol-level interfaces; monitor and document production models.

Responsible for designing, building, and operating AI-powered features, scalable APIs, and maintaining integrations within ClickHouse's AI/ML ecosystem.

As an MLOps/ML Platform Engineer, you will build and manage ML systems, optimize workloads, and ensure production model reliability while collaborating across teams.

As a Senior Machine Learning Engineer, you will develop and deploy ML models for health data analysis, collaborating with cross-functional teams to ensure reliability and regulatory compliance.

Design and implement ML infrastructure for scalable deployment, collaborate across teams, optimize ML systems, and enhance tooling.

As an Applied Machine Learning Platform Engineer, you'll design and maintain training infrastructure, manage distributed pipelines, and optimize data workflows for machine learning models.

As a Senior Machine Learning Engineer, you'll design and develop infrastructure and models for AI-powered applications while collaborating with teams to enhance product functionality.

The VP of Research, Machine Learning will set research direction for AI systems, focusing on context representation, reasoning, and evaluation frameworks while ensuring product safety and alignment.

Responsible for building and maintaining end-to-end ML pipelines and deploying production-grade ML systems. Tasks include model fine-tuning, evaluation, and collaboration with engineering teams.

Lead computer vision projects and develop ML models for power grid analysis while mentoring engineers and ensuring software quality standards.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

The AI Director will oversee ML bot development and implementation, identify AI opportunities, educate teams, and prototype AI solutions.