Top Machine Learning Jobs in Raleigh, NC

Deploys and optimizes enterprise infrastructure across on-premises systems, networks, AWS, Azure, and Microsoft 365. Engineers Terraform automation, Intune endpoint management, AI initiatives, SaaS integrations, SSO, and IT service workflows. Designs and maintains cybersecurity architecture, Zero Trust controls, security baselines, monitoring, and compliance controls aligned with CIS, NIST, and SOC 2. Provides advanced troubleshooting, technical support, VoIP administration, vendor coordination, and root-cause remediation.

Manage the AI opportunity roadmap for Risk Services, prioritizing use cases, coordinating internal data science teams and external vendors, translating business needs into requirements, and supporting AI governance, compliance, explainability, auditability, implementation, adoption, and benefits realization. The role focuses on business outcomes and solution delivery rather than hands-on model development.

Designs, develops, deploys, maintains, and optimizes ETL processes and cloud-based system integrations for healthcare data warehousing and business intelligence. Works with DHA and Cerner inpatient and outpatient data, develops database procedures, validates migrations, performs data mapping and modeling, and supports data science and machine learning teams. The role also documents processes, tunes performance, captures client requirements, and manages data transformation initiatives.

Own and develop SandboxAQ’s intellectual property function, including patent portfolio strategy, invention harvesting, prosecution, lifecycle management, outside counsel oversight, freedom-to-operate analyses, trademark clearance, and trade secret programs. Partner with scientists, engineers, and business teams to protect innovations, inform product strategy, support transactions, and build scalable IP processes in a fast-growing AI-focused company.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

Own the research-to-production pipeline: harden training/evaluation workflows, build packaging/deployment tooling, design release gates, optimize inference and serving for latency/throughput, establish benchmarking and validation, and instrument feedback from production to accelerate research iteration.

Design, develop, and deploy machine learning models and pipelines to optimize operations. Lead full ML project lifecycle, ensure model evaluation/monitoring, collaborate cross-functionally, mentor junior engineers, and drive continuous improvement in ML applications and processes.

Own complex customer escalations from troubleshooting through resolution across web services, APIs, SDKs, databases, and integrations. Diagnose issues using logs, network traces, code debugging, and technical tools; collaborate with Support, Product, and Engineering to identify root causes and document bugs. Apply AI-powered diagnostics and machine learning to detect patterns and automate troubleshooting. Create technical documentation, prioritize cases, and communicate solutions to technical and non-technical audiences.

Advise clients on antitrust eDiscovery compliance using machine learning and generative AI. Build and validate TAR/AI models (Epiq AI, Relativity, Reveal, Brainspace), craft LLM prompts, draft defensible protocols, train/transfer workflows to review teams, and support client-facing, pre-sales, and thought-leadership activities. Must manage multiple projects and meet deadline-driven schedules.

Leads and scales the post-sale customer success organization, overseeing customer retention, expansion, adoption, renewals, and customer outcomes. Manages 20 or more Customer Success Managers and Leads, develops scalable lifecycle processes, integrates AI into customer success operations, and partners cross-functionally on product and revenue strategy. The role also manages strategic accounts, international expansion across Mexico and Latin America, team development, performance metrics, customer advocacy, and operational excellence.

Develop and deploy NLP and machine learning models for classification, sentiment analysis, entity extraction, information retrieval, and user intent detection across large-scale legal, financial, news, and business datasets. Design scalable data science pipelines, evaluate modern AI algorithms and tools, translate business needs into technical solutions, and collaborate with product and engineering teams. Mentor junior scientists and contribute to model deployment, monitoring, maintenance, and development best practices.

Manage paid media strategies and campaigns across search, social, display, and programmatic channels. Advise clients using integrated paid, organic, and analytics data; oversee campaign performance, keyword research, ad copy, landing page recommendations, and presentations. Build client relationships, mentor account associates, collaborate with SEO and data teams, and use AI to improve workflows and outcomes.

Develop and lead paid media strategies across search, social, display, and programmatic channels. Manage campaign strategy, performance analysis, testing, optimization, and integrated paid and organic recommendations. Consult with clients, present results, build relationships, mentor account associates, and identify data-driven growth opportunities. Use AI tools to improve workflows and contribute insights across the team.

Lead strategy to define, measure, and evolve Solution Engineer and Cloud Solution Architect excellence for Microsoft Security. Use data, AI-powered analytics, and customer insights to identify performance drivers, design capability strategies, advise senior leaders, and drive field transformation. Build governance, risk remediation, and scalable enablement programs while partnering across engineering, product, sales, and enablement to measure impact and continuously improve outcomes.

Design, build, and deploy production-ready intelligent solutions using machine learning, deep learning, generative AI, and large language models. Develop RAG pipelines, integrate AI services, manage model deployment and MLOps workflows, and apply strong software engineering practices. Collaborate with engineering, product, and data teams in a distributed environment to create scalable, reliable, responsible AI-powered products.

As a Senior Machine Learning Engineer, you will design and implement systems for ML and NLP, optimizing models and tools for Clover's healthcare solutions.

As a Senior Fullstack Engineer, you'll architect and build a high-concurrency auction engine, leveraging AI for enhanced user experiences and system reliability.

Designs and operates scalable data infrastructure, pipelines, backend services, and cloud platforms powering LLM, machine learning, analytics, and experimentation workflows. The role develops Python services, APIs, data models, retrieval-augmented generation capabilities, vector search, and production AI systems. Responsibilities include data quality, observability, security, Infrastructure as Code, CI/CD, architecture, documentation, cross-functional collaboration, technical leadership, and mentoring across PlayStation Studios.

Leads development, deployment, and scaling of AI and machine learning solutions across business units. Drives generative AI and LLM innovation, collaborates with cross-functional and global data science teams, and supports integration of AI tools across platforms. The role requires hands-on technical contribution, strategic leadership, experimentation, stakeholder communication, and adoption of best practices in data science and AI transformation.

Leads AI-enabled Finance transformation initiatives from roadmap development through implementation and adoption. The role analyzes Finance processes, identifies automation opportunities, documents requirements, coordinates cross-functional Technology and Finance teams, manages change and training, tracks ROI and KPIs, and supports governance, compliance, SOX controls, and system integration across enterprise applications.

Lead partner marketing with consulting and systems integrators to drive joint GTM plans, co-marketing programs, repeatable partner collateral, customer stories, partner communications, and measurable pipeline growth.

Lead a team of safety engineers to define and execute AV safety strategy across development, simulation, testing, and deployment. Apply UL4600/ISO standards, develop safety cases, set safety metrics (SPI), manage safety plans and artifacts, train engineers, and coordinate with partners and stakeholders to validate ML models and ADS integration for safe public-road operation.

Designs statistical analysis plans and validates machine learning models using rigorous performance, calibration, uncertainty, subgroup, fairness, and longitudinal analyses. Applies biostatistical methods to healthcare data, documents assumptions and limitations for auditability and regulatory readiness, and translates complex findings into clinically meaningful insights. Collaborates with engineering, machine learning, data, clinical, and product teams.

Leads technical strategy and product adoption for major Retail and CPG enterprise accounts as Databricks’ primary technical voice. Partners with account executives, guides customers through data and AI transformations, builds technical champions, aligns solutions to business strategies, and mentors team members. Requires extensive pre-sales, big data, cloud, data science, programming, and production data systems experience.

Designs and deploys AI/ML solutions from prototype through production for government clients. Responsibilities include generative AI using LLMs and RAG, intelligent classification, agentic frameworks, AI coding tools, legacy-system integration, and automated reporting. The role also establishes AI/ML roadmaps, scales adoption, communicates technical concepts to stakeholders, and mentors data scientists.