Top Machine Learning Jobs in Raleigh, NC

Design and implement data-centric cybersecurity solutions: develop ML algorithms and automation for security tools; discover, parse, map, and transform legacy RMF artifacts into OSCAL; migrate and analyze security data; reproduce dashboards/workflows in eGRC; collaborate with Professional Services; produce migration assessments and reports.

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

Lead the development of deep learning models for email data, optimize models, design evaluation frameworks, integrate products, and mentor junior researchers.

Lead statistical activities for clinical trials from protocol design through reporting. Provide statistical oversight, collaborate with cross-functional teams and CROs, apply SAS/R (and ML) for analyses, automate processes, and mentor junior statisticians.

Lead engineering strategy and delivery for customer-facing web and mobile platforms; drive AI-native transformation, increase conversion and speed-to-fund, raise engineering talent and velocity, ensure secure and compliant architectures, partner with product and cross-functional teams to deliver measurable business outcomes.

Lead onboarding and training for new customers of an AI-powered construction SaaS. Customize training, run webinars and office hours, create documentation, drive user adoption, surface issues with support, and collaborate with product and customer success to refine onboarding processes.

Lead strategy, roadmap, and delivery for Tekmetric's SaaS product for auto repair shops. Own user research, AI/ML product initiatives, cross-functional alignment, go-to-market coordination, and measurement of business outcomes. Train internal teams and iterate on features from concept through launch and optimization.

Lead design and production deployment of ML models focused on pricing, availability, forecasting, and optimization. Build data infrastructure, governance, testing/monitoring, and dashboards. Partner with executives and cross-functional teams, mentor others, and establish scalable data-science practices and experimentation frameworks.

Operate and improve enterprise AI/ML platforms across Palantir Foundry, AWS Bedrock, and Amazon SageMaker. Responsibilities include deployment, monitoring, observability, automation, governance, model lifecycle management, incident response, root cause analysis, CI/CD, infrastructure as code, and production reliability. The role provides technical leadership and mentorship while partnering with data, infrastructure, security, architecture, product, and engineering teams to support cloud-based AI workloads and Generative AI adoption.

Lead and grow a team of Conversation Designers to build and scale conversational AI experiences. Partner with Product, Engineering, Analytics, and ML teams to drive strategy, tooling, evaluation, and quality practices. Recruit and remove roadblocks, own strategic initiatives, and remain hands-on in designing, testing, and improving AI-driven conversational products.

Lead and scale teams building offensive and defensive AI agents and the ML, data, and safety systems that power them. Drive strategy, production-grade engineering, safety and governance, cross-team collaboration, and hiring/leadership development to deliver secure, reliable agentic security capabilities for customers.

Lead product marketing for PolyAI's voice assistant products: define messaging and positioning, drive go-to-market strategy and enablement, build competitive intelligence, develop personas and sales collateral, run customer and market research, support revenue enablement, scale and lead the product marketing team, and act as an external spokesperson.

Lead full sales cycle to drive CTV performance advertising growth in North America: prospect, close, launch and scale CTV budgets, manage key advertiser relationships, collaborate cross-functionally, represent Jampp at events (20% travel), and provide local feedback to improve global initiatives.

Lead development and deployment of cutting-edge ML models for pricing, design and analyze experiments, collaborate with product and engineering, present findings to stakeholders, and lead technical projects to influence team output and business metrics.

Senior Business Systems Analyst responsible for capturing functional requirements for agent-facing servicing applications, defining integrations/APIs with core banking systems, translating needs into user stories and acceptance criteria, supporting testing and releases, analyzing workflows to improve agent productivity, and identifying AI/ML opportunities for fraud detection and automation.

Lead development and optimization of web scraping pipelines to extract, clean, and store large-scale web data. Handle dynamic content, pagination, distributed scraping, database design with NoSQL, deploy jobs to cloud, and monitor systems for reliability and data quality. Support ML-based data cleaning and categorization.

Lead end-to-end enterprise customer engagements and onboarding for large insurance clients, run program timelines and executive reporting, design and deploy AI agents and internal tooling, own the CE operations roadmap and knowledge base, drive cross-functional resolution of technical/operational issues, and continuously improve efficiency and quality across the Client Engagement team.

Lead product strategy and execution for data and AI platforms, driving GenAI/LLM initiatives, cross-functional collaboration, responsible AI governance, experimentation (A/B testing), measurement of model impact, and mentoring product teams to embed scalable ML capabilities into clinical and member experiences.

Own pre-sales technical engagement: consult customers, deliver technical presentations and demos (web, iOS, Android), lead POCs, support RFP/RFI responses, manage onboarding and integrations, and advise sales, product, and engineering teams on implementation and value realization.

Design, build, and scale backend systems and APIs for high-transaction consumer products. Collaborate with product, credit, compliance, support, and analytics teams. Contribute to code reviews, technical planning, security, and operational excellence. Mentor peers and promote engineering best practices.

Lead the development and implementation of machine learning solutions, managing a team to drive strategic decisions and innovative business outcomes.

Design, implement, and scale ML-based solutions for search and advertising; define data collection, evaluation, and production serving strategies; analyze data to inform development; communicate cross-functionally; produce technical reports; and stay current with advances in LLMs, vision models, and generative AI.

Design and evaluate memory architectures for foundation models across modalities. Build production-ready, scalable learning models, define memory metrics, collaborate with researchers, and recommend roadmap improvements for long-horizon behavior and efficient storage/retrieval.

Design and evaluate general memory architectures for foundation models across modalities. Develop production-ready, scalable learning models, define memory evaluation metrics, and collaborate with researchers to roadmap improvements.

Lead AI/ML efforts for US Commercial finance: design and execute prompt engineering and LLM experiments, translate finance processes into AI technical specifications, validate solutions against workflows and SOX controls, support data solutions and troubleshooting, and manage portfolio-level metrics and executive dashboards while acting as the finance SME for technical teams.