Top Machine Learning Jobs in Little Rock, AR

Lead the development and integration of advanced AI solutions, focusing on scalable AI models and collaborating with cross-functional teams.

As a Senior Machine Learning Engineer, you will design and deploy ML models to optimize clinical trial workflows, mentor junior engineers, and collaborate with cross-functional teams to enhance patient engagement.

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

As a Staff Machine Learning Engineer, you will develop, productionize, and deploy ML models for clinical use, ensuring real-world effectiveness through hands-on coding and infrastructure building.

The role involves improving machine learning ranking models, implementing algorithms, and taking full ownership of machine learning systems within Quora's product.

The ML Engineer will leverage deep learning for natural language processing tasks, impacting Entefy's products while requiring strong machine learning fundamentals and NLP expertise.

The Staff Machine Learning Engineer will develop and maintain MLOps tools, optimize model performance, and collaborate on ML system architecture with a focus on enhancing developer experience.

The Enterprise Account Executive will drive revenue by engaging with enterprise insurance clients, managing the sales cycle, and fostering strategic relationships with executives, leveraging Vellum's data analytics platform.

As Director of AI/ML, lead the ML organization, set technical vision, mentor a high-performing team, and contribute to model development and production deployment.

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.

As a Staff Machine Learning Engineer, you will optimize Quora's ad products by applying machine learning algorithms, taking ownership of systems, and collaborating across teams.

As a Senior MLOps Engineer, you will manage production ML systems, define lifecycle strategies, optimize ML pipelines, and collaborate with cross-functional teams to enhance ML operations.

You will lead technical strategy and engineering for ML-powered messaging features at Airbnb, integrating solutions and collaborating with teams to enhance user communication. Responsibilities include system design, mentoring, and establishing engineering standards.

The AI Forward Deployed Engineer designs and implements AI solutions, collaborating with stakeholders, enhancing reliability, and producing reusable resources. Responsibilities include diagnosing AI solution issues and engaging with finance and data teams.

Design and build machine learning models for Zillow's product features, optimize AI components, and mentor engineers within a cross-functional team.

As a Senior Machine Learning Engineer, you will design and train ML models for logistics, manage their production deployment, and optimize their performance while collaborating with the data science team.

As a Machine Learning Engineer, you will design and build AI capabilities, develop scalable ML infrastructure, and collaborate on production systems in the real estate domain.

Lead architecture and engineering for production-grade ML in healthcare: design MLOps CI/CD, scalable low-latency inference for LLMs and classical models, build reliable data pipelines for FHIR/HL7/DICOM, manage cloud IaC and observability, ensure HIPAA/HITRUST compliance, and mentor engineering teams to operationalize agentic AI workflows.

The Senior ML Engineer will design evaluations for AI features, optimize pipelines, and ensure quality in ML systems while collaborating with cross-functional teams.

The role involves deploying and optimizing AI/ML models, integrating them into products, building APIs, and ensuring reliability through testing and monitoring. Candidates will work in a collaborative environment to enhance their MLOps and software skills.

The Staff Machine Learning Engineer will lead AI initiatives, architect LLM systems, design evaluation frameworks, and mentor engineers.

Build and maintain MLOps pipelines, deploy and monitor ML models as scalable services, transform and integrate healthcare data (FHIR/HL7), ensure reproducible feature management, and uphold HIPAA/HITRUST security for production ML in clinical systems.

The Customer Success Manager will manage post-sales relationships, drive customer engagement and ROI, and advocate for client needs within the Buzz Solutions platform.

The Machine Learning Operations Engineer develops backend pipelines for deploying ML models, builds Docker containers, manages Kubernetes on GCP, and integrates APIs. Responsibilities include performance monitoring, documentation, and collaboration with software engineers.

The Machine Learning Engineer will design and build systems that improve the AI shopping agent by using real user feedback, focusing on feedback loops and metrics to enhance user interactions and agent performance.