Machine Learning Jobs in Durham, NC

Develop and optimize GPU-accelerated generative AI training and inference workloads on NVIDIA platforms. Collaborate with developers, academia, and internal engineering teams to improve algorithms, frameworks, low-level libraries, hardware, and software performance. Analyze CPU and GPU architectures, contribute to open-source projects, and communicate innovations through technical publications and conferences.

Verify ASIC inference accelerator designs at block and SoC levels using advanced methodologies, random stimulus, functional coverage, assertions, and UVM. Develop verification infrastructure, debug designs, optimize automated flows, and collaborate with architects, designers, and pre- and post-silicon teams. Apply knowledge of ASIC design flow, power verification, DFT, netlist verification, and machine learning techniques to improve verification processes.

Leads the enterprise Workday platform and HR technology strategy, roadmap, governance, operational support, integrations, reporting, security, and continuous improvement. Oversees service delivery, release readiness, audit and SOX compliance, vendors, cross-functional programs, and platform-related risk. Partners with HR, Facilities, Finance, IT, Security, Legal, and Audit while leading a multidisciplinary team and evaluating AI opportunities. The role requires executive stakeholder management, strong Workday expertise, product leadership, and experience in complex regulated environments.

Lead legal counsel for AI and machine learning matters, advising engineering and product teams on intellectual property, regulatory compliance, contracts, privacy, open-source licensing, product design, and risk mitigation. Develop AI/ML legal playbooks, compliance processes, training, and IP protection strategies while collaborating with cross-functional stakeholders and presenting emerging risks to executives and the Board.

Leads marketing measurement strategy and develops scalable frameworks for attribution, Marketing Mix Modeling, incrementality testing, experimentation, forecasting, and predictive analytics. Builds unified marketing data models, governs KPIs and tracking standards, creates executive reporting, and translates complex analyses into business recommendations. Partners cross-functionally with marketing, engineering, IT, privacy, and analytics teams while evaluating measurement technologies and vendors. Acts as the subject matter expert and helps scale the marketing analytics and data science function.

Manage NVIDIA’s global Lenovo OEM account and drive adoption and integration of NVIDIA accelerated computing platforms. Develop technical expertise across AI hardware, networking, software, and reference architectures; identify solution opportunities; package NVIDIA technologies into Lenovo offerings; and develop co-marketing and co-selling strategies. Coordinate product, engineering, supply planning, pricing, quality, and go-to-market teams while building relationships with senior stakeholders and supporting cloud and enterprise sales channels.

Leads enterprise Finance systems strategy and transformation, owning the multi-year roadmap, technology architecture, AI and automation initiatives, data governance, platform evaluations, and complex cross-functional programs. Partners with Finance, IT, data, security, and architecture teams to modernize processes, deliver measurable outcomes, ensure governance and controls, and drive adoption. Mentors 1–3 direct reports while advising executives across global Finance functions.

Software Engineering Interns will design, build, test, and improve production enterprise SaaS software across frontend, backend, APIs, data, AI-enabled features, and platform engineering. Responsibilities include developing user interfaces and backend services, integrating databases and APIs, processing data and documents, improving performance and scalability, writing maintainable code, participating in reviews and testing, and collaborating with engineering and cross-functional teams in an Agile environment.

Architects and develops secure, scalable AI/ML systems and MLOps infrastructure across distributed cloud environments. Builds model training, inference, monitoring, governance, adversarial robustness, federated learning, and multi-agent safety capabilities. Designs agentic workflows, data and ETL pipelines, model lifecycle automation, and high-performance serving systems. Evaluates reliability and security under real-world and adversarial conditions, collaborates with cybersecurity and cloud teams, and mentors engineering teams on advanced machine learning and secure development practices.

Lead an R&D ML team to develop and deploy AI/ML solutions for semiconductor manufacturing. Guide cross-functional research, mentor engineers in computer vision, physics-informed ML, and reinforcement learning, and apply materials science expertise to advance product development.

Leads enterprise risk oversight for alternative investment strategies, including hedge funds, private equity, private credit, venture capital, structured credit, real assets, digital assets, and derivatives. Builds risk frameworks, stress testing, scenario analysis, valuation controls, reporting, governance, and advanced analytics. Manages a high-performing risk team and partners with investment, finance, treasury, technology, and executive stakeholders to assess market, credit, liquidity, valuation, concentration, operational, and emerging risks.

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.

Lead the development of AI-powered applications, mentoring engineers, architecting scalable systems, and driving innovation in healthcare technology.