Top Machine Learning Jobs in Little Rock, AR

Leads client-facing generative AI and data modernization engagements, directing solution design, delivery planning, architecture, and technical decisions. Guides teams in prompt engineering, context engineering, agent orchestration, LLM evaluation, RAG, vector databases, and AI guardrails. Oversees cloud AI implementations using Gemini, Vertex AI, AWS Bedrock, or Azure AI Services; develops Python prototypes; evaluates model performance; manages workstreams and deliverables; and mentors staff on AI methods, agile delivery, and technical problem-solving.

Leads engineering teams delivering scalable AI and machine learning solutions on Google Cloud. Oversees generative AI architecture, Vertex AI, LangChain, LangGraph, LLM APIs, RAG, experimentation, evaluation, guardrails, and LLMOps. Guides technical strategy, client alignment, delivery execution, and team development while applying Python, data science, and machine learning methods to build reliable AI products.

Leads Google Cloud AI and machine learning engineering teams and client workstreams. Oversees generative AI, LLM application, agent orchestration, retrieval-augmented generation, model evaluation, prompt engineering, guardrails, and LLMOps initiatives. Reviews architecture, code quality, testing, and solution delivery using Vertex AI, LangChain, LangGraph, Python, and LLM APIs. Coaches team members, improves reusable delivery assets, and manages client relationships, timelines, quality, and expectations.

Leads client-focused generative AI and data modernization architecture, translating business needs into scalable solutions using Google Cloud, Vertex AI, LLMs, vector databases, and modern data platforms. Advises stakeholders, develops AI evaluation and guardrail practices, guides experimentation and deployment, presents technical recommendations, supports proposals, and coaches teams through complex transformation programs.

Build scalable systems and machine learning models that transform satellite imagery into labeled geospatial data and production computer vision products. Responsibilities include developing data and annotation pipelines, tracking lineage and versioning, deploying inference services, evaluating models, supporting cloud infrastructure, and improving labeling workflows. The role requires strong Python, cloud, containerization, CI/CD, infrastructure-as-code, production support, and deep learning expertise, with preferred experience in GCP, Vertex AI, spatial databases, and satellite imagery.

Own and scale Jellyfish’s security engineering program, including strategy, architecture, secure SDLC governance, AI security, threat modeling, vulnerability remediation, incident response, penetration testing, and bug bounty programs. The role combines hands-on software development with executive advising, cross-functional leadership, mentorship, and security risk management across SaaS infrastructure and customer-facing AI products.

Drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, machine learning, NLP, LLM applications, and classifier implementation. Build growth metrics, monitoring pipelines, evaluation datasets, and AI trigger systems across search and Duck.ai. Analyze privacy-constrained data, deploy production-grade models, optimize SQL queries, and lead complex projects from scoping through production with minimal direction.

Own the strategy, roadmap, requirements, launch, adoption, and success metrics for a technical platform. Partner with engineering, data, product, and business teams; evaluate architecture, APIs, and system tradeoffs; prioritize foundational investments against customer and revenue outcomes; and apply AI to improve platform capabilities. The role requires strong product management experience, technical depth, analytical skills, and production experience with LLM-based or ML-adjacent products.

Lead AMP's multidisciplinary engineering organization to define and execute technology vision and roadmap. Responsible for scaling teams across hardware, software, AI, and infrastructure; driving product development, quality systems, and reliable deployments; partnering with execs and cross-functional teams on budgets, prioritization, and metrics; recruiting and mentoring leaders; and balancing short-term delivery with long-term investments to create business value.

Lead product design for Fetch’s Receipt & Rewards experience, connecting receipt capture, account linking, recognition, matching, and rewards. Define design strategy for complex, AI-enabled systems; improve usability, accessibility, trust, and experience quality; and balance user needs, data quality, business goals, and technical constraints. Partner with Product, Engineering, Research, and Data Science, drive cross-functional alignment, shape multi-quarter initiatives, and mentor designers.

Designs, builds, scales, and operates distributed CI/CD services supporting millions of builds, tests, and releases. Develops code for Azure-based infrastructure spanning virtual machines, containers, and custom lab environments. Responsibilities include requirements analysis, architecture and design documentation, estimation, debugging, optimization, operational playbooks, on-call incident response, monitoring, reliability improvements, and mentoring engineers.

Design, develop, and operate scalable software platforms and automation for Azure network qualification infrastructure. Build tools for device provisioning, configuration, lifecycle management, testing, telemetry, and health validation. Develop AI-powered agents for troubleshooting, root-cause analysis, and engineering productivity. Create reliable distributed systems with observability, diagnostics, automated recovery, and scalability while collaborating across software and network engineering teams.

Provides technical leadership for architecture and evolution of large-scale distributed data platforms supporting Azure network telemetry. Designs streaming and batch systems, establishes reusable engineering patterns, drives cross-team technical strategy, and owns capabilities from design through production operations. Ensures scalability, reliability, security, performance, data quality, and operational excellence while mentoring engineers and influencing technical leaders. The role also involves architectural reviews, dependency management, risk reduction, and applying AI or machine learning approaches to operational systems.

Leads the property insurance product roadmap for Prometheus, owning prioritization across underwriting, accumulation, and portfolio workflows. Builds and manages the Product team, translates carrier needs into precise requirements, validates releases in customer workflows, and drives adoption. Owns insurance model governance, including validation, documentation, change control, and AI-use policies. Requires deep property insurance, catastrophe modeling, geospatial, machine learning, and enterprise product experience.

The Commercial Legal Director will lead complex technology and commercial transactions, negotiate SaaS, licensing, partnership, marketing, and services agreements, and develop scalable legal contracting standards. The role advises teams on AI, intellectual property, privacy, security, and regulatory issues; improves contracting workflows using Ironclad and AI-enabled tools; and partners with senior stakeholders across product, engineering, finance, marketing, and people operations.

Own analytics for Root’s Customer Experience domain and policyholder retention. Develop metrics, analytical frameworks, experimentation systems, and strategic recommendations. Partner cross-functionally with Product, Engineering, Data Science, and Operations to shape roadmaps, evaluate customer initiatives, quantify business impact, and influence senior leadership decisions through rigorous analysis and clear communication.

Build and scale Pulse’s technology partner ecosystem by recruiting and signing partners, structuring integrations and commercial agreements, developing joint go-to-market and co-sell programs, and driving partner-sourced pipeline, revenue, and API usage. The role also manages partner onboarding, enablement, deal attribution, forecasting, technical validation, and feedback to product and engineering teams.

Lead and grow a global engineering team building endpoint visibility, prevention, and on-device ML across Windows, macOS, and Linux. Own roadmap and delivery, direct model development and telemetry, drive cross-platform protection parity, coordinate with product and partner teams, and represent the team externally through research and conferences.

Own the strategy, roadmap, and delivery of AI-powered capabilities across Mapbox Maps. Partner with engineering, customers, and cross-functional teams to identify use cases, prioritize development, validate solutions, and launch products. Manage pricing and packaging, sales enablement, marketing, trials, and partnerships while driving customer adoption, business growth, and scalable experiences for developers and end users.

Lead analytics partner to Community Support, driving data-driven roadmaps, scalable reporting and measurement, causal inference and experimentation, and improvements to agent/guest/host experiences via analytics, modeling, and stakeholder influence.

Own the platform powering Airbnb’s AI Assistant, including request routing, knowledge retrieval, capabilities, actions, and evaluation. Set product strategy, define resolution and quality standards, analyze production data, diagnose system failures, and guide engineering, data science, policy, and knowledge partners. Lead generative AI launches, safety and readiness reviews, LLM evaluation systems, calibration, and certification while aligning cross-functional teams and communicating decisions to executives.

Owns the intelligence platform roadmap for enterprise healthcare engagement, including decisioning, orchestration, integrations, interoperability, identity and consent management, and scalable deployment. The role defines strategy and requirements, prioritizes platform investments, leads partner integrations, establishes success metrics, and coordinates Engineering, AI/ML, Data Science, Security, Design, and client teams. It also embeds healthcare compliance, security, and responsible AI throughout the product lifecycle.

Own the enterprise AI strategy, roadmap, governance, investment priorities, and measurement framework. Identify and prototype high-value AI use cases, guide pilots into production, establish responsible-AI standards for sensitive data, and communicate outcomes to executives. Build adoption through enablement and reusable practices while coordinating technology, business, legal, security, data, and vendor partners. Lead the emerging AI strategy function and hold teams accountable for delivery and value realization.

Advise Product, Engineering, Security, and business teams on software, SaaS, cloud, privacy, cybersecurity, AI, intellectual property, and emerging technology regulations. Guide products throughout their lifecycle, assess legal and regulatory risks, draft agreements and privacy documentation, support privacy-by-design, monitor global regulations, and develop scalable legal processes, playbooks, policies, and training.

Develop and deploy statistical and machine learning models for credit risk, delinquency, defaults, loan losses, underwriting, and risk-based pricing. Analyze credit bureau, alternative, and loan performance data; build production-ready analytical pipelines; monitor model performance; and address data anomalies. Lead complex initiatives, mentor colleagues, document methodologies, and incorporate model governance, fair lending, privacy, and responsible AI considerations while partnering with Credit Risk, Product, Engineering, and Finance.