Top Remote Machine Learning Jobs in Fayetteville, AR

Lead product discovery, requirements, prioritization, and delivery for data, analytics, reporting, and intelligence capabilities. Work closely with Engineering, Data, Analytics, Product Operations, and client teams to translate needs into clear user stories, acceptance criteria, and backlog priorities. Improve reporting accuracy, data quality, analytics usability, and enable early AI/ML capabilities while ensuring delivery readiness and stakeholder alignment.

Lead technical execution across backend, frontend, mobile, AI, and data. Translate ambiguous product goals into technical plans, unblock hard engineering problems, coordinate cross-domain work, raise engineering quality, define hiring needs and technical evaluation standards, and build internal AI workflows to foster an AI-native engineering culture.

As a Machine Learning Engineer II, you will enhance AI systems for automating customer operations, develop evidence extraction pipelines, and collaborate with teams on model development and deployment.

Lead the machine learning strategy, design scalable ML systems, drive MLOps, mentor engineers, and comply with AI governance.

Independently validate and monitor machine learning models for credit underwriting, credit risk, and fraud detection. Identify model weaknesses, recommend improvements, and collaborate with model owners to remediate findings. Support and maintain the Model Risk Management framework and coordinate with Internal Audit, Internal Controls, and Compliance on audit and regulatory requests.

Lead development and roadmap of AI-powered products for internal teams and advertisers, translating AI concepts into product requirements, partnering with engineering, data science, sales, and ad ops to launch targeting, creative, analytics, and automation solutions.

Research, deploy, and maintain AI models and automation solutions; integrate systems and APIs; manage AWS infrastructure and PostgreSQL databases; build BI dashboards; monitor and optimize AI systems and provide technical support.

The AI Executive Partner will advise C-Suite executives on leveraging AI to drive business outcomes, manage member relationships, and deliver innovative AI solutions.

Lead and deliver complex, cross-team AI product programs, drive agent-first SDLC adoption, ensure integration and operational readiness of AI workflows, define metrics, communicate risks and status, and standardize TPM best practices across Product and Engineering.

Design, develop, and implement secure, scalable cloud systems (Azure/AWS); perform system engineering, risk assessments, and NIST-compliant ATO/ATD processes; manage secure data ingestion and orchestration; integrate AI/ML concepts; secure communications and network infrastructure; present technical findings to senior USG leadership and provide hands-on support.

Lead end-to-end healthcare fraud investigations for Clover's Medicare Advantage business. Own caseloads, gather and analyze claims and medical evidence, coordinate legal support, prepare defensible referral packages, leverage AI and analytics tools, and collaborate cross-functionally to drive recoveries and provider actions.

Lead architecture and implementation of high-performance software to deploy and operate AI/ML models for network threat detection. Build autonomous AI agent workflows, production ML pipelines, and services; drive cross-team engineering standards, mentor engineers, and represent technical direction to leadership.

Develop and maintain scalable, performant web applications and data pipelines. Collaborate with engineering managers, product, and stakeholders using Agile practices. Emphasize observability, testing, CI/CD, security, and incremental releases to deliver robust production systems.

Contribute data science and statistical expertise to design analytical challenges, create high-quality training data, evaluate AI-generated solutions, build evaluation frameworks, and collaborate with researchers to improve LLM quantitative reasoning and model performance.

Own growth and performance for Kits AI across funnel optimization, activation, retention, pricing, and monetization. Productize ML capabilities into creator-facing workflows, partner with research and engineering, run experiments and analytics (e.g., Amplitude), conduct customer research, and leverage AI tools to accelerate shipping and internal insight systems.

Evaluate and strengthen AI model behavior on cybersecurity topics by writing expert prompts, annotating and grading model responses for accuracy and safety, and applying structured guidelines to classify sensitive content. Work part-time on AI safety tasks with emphasis on secure, responsible handling of dual-use information.

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.

As a Systems Architect, you'll define and drive the infrastructure architecture for AI/ML workloads, design multi-cloud strategies, manage compute orchestration and storage systems, and lead capacity planning, while also collaborating with engineering leadership.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

As a Senior Impact Analyst, you will analyze sustainability challenges, design and manage interventions, and work closely with smallholder communities, emphasizing rigorous research and collaboration.

Design, develop, test, and deploy RPA/AI agent solutions (UiPath/Blue Prism) integrated with enterprise systems. Analyze business processes, estimate feasibility, create maintainable automation workflows, document solutions, support UAT/rollout, and troubleshoot production automations. Collaborate with stakeholders, manage integrations (APIs/SQL/WebServices), and ensure quality using unit testing and source control.

The AVP, Digital Portfolio Management oversees P&L for small business products, driving underwriting profitability and digital transformation through analytics, cross-functional collaboration, and strategic initiatives.

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

Seeking a Senior Full Stack .NET Developer to work on a social good project, with strong skills in C#, AngularJS, design, and UX. Requires 5+ years of experience.

The Data Scientist II will design, build, and deploy machine learning models and data products, translating business problems into data-driven solutions, while collaborating with various stakeholders and ensuring reliable, production-ready outcomes.