Top Machine Learning Jobs in Raleigh, NC

Serve as Business Analyst/Product Owner to shape product roadmaps, gather and document requirements, prioritize backlogs, participate in Agile ceremonies, partner with UX and engineering, validate delivered functionality, support UAT/troubleshooting, monitor usage/analytics, create product documentation and training, and deliver product demonstrations to stakeholders and clients.

Individual contributor applied GenAI engineer/data scientist leading ML projects end-to-end. Builds and productionizes LLM and ML solutions, partners with business stakeholders, identifies AI/ML use cases, manages multiple projects, and communicates results with clear visualizations to deliver measurable business impact.

Design, automate, configure and qualify customer use cases on IOS‑XR platforms (ASR9K, NCS5500, 8000). Reproduce customer environments in lab, develop test frameworks and web GUIs leveraging analytics/ML, run automated and manual validation tests, troubleshoot routing platforms, and collaborate globally with development and account teams to deliver validated solutions for large service provider and enterprise deployments.

Lead bench-scale heterogeneous catalyst discovery for renewable fuels: design and synthesize iron-based Fischer-Tropsch and non-noble hydrodeoxygenation catalysts; perform end-to-end characterization (XRD, BET, TPR/TPD, chemisorption, XPS, TGA, TEM); deliver ML-ready experimental data to the platform; support 100 g scale-up and bench-pilot demonstrations; maintain rigorous, safety-focused laboratory practices.

Lead R&D for next-generation image and video coding using ML/AI. Design and implement video algorithms, codecs, and multimedia workflows, represent Disney in standards bodies, drive architectural innovation, and produce IP while collaborating globally across media processing, encoding, and streaming domains.

Drive go-to-market and enterprise software sales for NVIDIA Agentic AI with Lenovo, packaging NVIDIA assets with Lenovo solutions, co-marketing and co-selling across direct and partner channels. Build technical understanding of accelerated computing and cloud-native stacks, develop ecosystem partnerships, lead three-way sales and marketing plans, and provide thought leadership at industry and customer events.

Design, implement, and monitor AI/ML models to improve underwriting risk assessment, pricing, and portfolio management. Translate underwriting rules into data models, integrate models into workflows, analyze datasets for risk patterns, build decision-support tools, ensure compliance and fairness, and collaborate with underwriting, actuarial, product, and engineering teams.

Design, implement, and optimize AI-powered solutions to support financial compliance and controls. Monitor GAAP/IFRS adherence, automate controls and reporting, support internal/external audits, and manage complex accounting areas like revenue recognition and lease accounting while collaborating with finance, audit, and technology teams.

Drive data-informed capital allocation by building financial models (NPV, IRR), applying AI/ML for forecasting and scenario planning, creating build-vs-buy and prioritization frameworks, implementing decision-support systems, collaborating with cross-functional stakeholders, and monitoring post-investment performance to refine allocation models.

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

Lead ITSM and digital transformation engagements, design and implement enterprise IT and cloud solutions (Azure, M365, virtualization, networking, security), manage stakeholders and project delivery, drive business development and sales, create client deliverables and roadmaps, mentor junior consultants, and maintain 1700 billable hours annually.

The Customer Success Engineer will lead deployments, serve as a technical advisor, and support customer engagement, focusing on product enhancements and user experience.

The Senior Machine Learning Engineer will develop core ML models, manage data pipelines, and collaborate with stakeholders to deliver scalable ML solutions.

Lead pre-sales technical engagements for Conversational and Generative AI solutions, collaborate across teams, and design value-driven demos for enterprise customers.

The Hyperscalers and Commercial Lead will develop technology-driven business strategies, drive customer adoption, and manage end-to-end sales processes while working closely with cross-functional teams.

Develop and experimentally validate novel ML architectures to improve prediction and design of in‑vivo molecular interactions, extending structure‑informed generative models to causal models and integrating with deployed drug‑design workflows.

Lead strategy and roadmaps for platform offerings that support robotics and autonomous systems. Drive customer discovery, define requirements and metrics, coordinate cross-functional execution, ensure production readiness, and lead adoption, rollout, and stakeholder communication for platform capabilities.

Join Nextdoor's machine learning team to build data-intensive products, develop ML models, analyze datasets, and enhance user experiences. Collaborate closely with product and data science teams.

The Chief Architect will lead the technical direction for Legion's Workforce Management platform, focusing on architecture decisions, AI systems, and scalable software solutions. Responsibilities include hands-on coding, technical leadership, and ensuring systems meet enterprise standards for performance and security.

Lead development and execution of MVB's AI and automation strategy, including Generative and Agentic AI and RPA. Partner with business and technical stakeholders to design, pilot, and scale solutions, establish governance and best practices, monitor performance metrics, manage vendors, and deliver training to ensure ethical, secure, and effective AI deployments.

The Solutions Engineer will provide technical support for customers, ensure satisfaction, communicate with sales, and analyze customer needs for product enhancements.

As the Engineering Lead, you will guide product strategy, manage and mentor engineers, and ensure successful execution in product areas, focusing on machine learning and technical expertise across teams.

The Product Manager will lead product development, working with cross-functional teams, driving growth, and creating user experience frameworks.

Manage a portfolio of customers as primary contact, drive adoption and retention, respond to support requests, troubleshoot issues with product teams, identify upsell and renewal opportunities, and provide customer insights to product and engineering.

Manage a portfolio of SaaS customers, build relationships, monitor usage, prevent churn, handle support and troubleshooting, identify upsell/renewal opportunities, and relay customer feedback to product and engineering.