Top Remote Machine Learning Jobs in Raleigh, NC

AVIA seeks experts in Digital Health and AI for advisory roles to support healthcare systems' technological transformations as part-time, project-based consultants.

The Product Marketing Manager will execute product launches and support go-to-market initiatives, collaborating with cross-functional teams to develop and deliver messaging and enablement materials targeting both technical and business stakeholders.

The Senior Product Manager will lead product initiatives, manage the product lifecycle, and ensure solutions meet customer needs while driving market growth and achieving KPIs.

Lead cross-functional strategic projects, build quantitative models and dashboards to track KPIs, align technical and commercial teams, audit and design scalable operational workflows, and synthesize technical and financial data into leadership-level presentations.

Lead data quality and data management for oncology studies, overseeing DM teams, vendor/CRO management, and compliance with CDISC/ICH-GCP. Develop risk management, integrate and surveil multi-source data, advise stakeholders on data collection and standards, produce metrics and dashboards, manage project resourcing and finances, review contracts, and deliver training to ensure high-quality, regulatory-compliant clinical and real-world data.

Lead and scale full-stack engineering teams for Yahoo Mail; define engineering vision and roadmap; drive AI-native development and AI transformation using Generative AI/LLMs and agents; partner with Product, Design, and Data Science to deliver scalable cloud-native mobile and web experiences; hire, mentor, and retain engineering talent while guiding architecture, technical reviews, and platform modernization.

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.

The Senior Product Architect will design security products, collaborating with product management and engineering teams, focusing on architecture and functionality for high-level product features.

The Vice President of Underwriting will lead the company's underwriting strategy, focusing on growth acceleration while managing credit, fraud, regulatory, and reputational risks. This role involves overseeing underwriting processes, implementing advanced analytics, optimizing risk frameworks, and ensuring regulatory compliance across different merchant segments.

Transfyr seeks adaptable builders for various roles across CS, biology, and business. Responsibilities include developing sensor stacks, data harmonization, computer vision, machine learning systems, lab operations, project management, and business development.

The Vice President of AI will define and lead the AI strategy at Tempo, integrating AI capabilities into products, building teams, and ensuring ethical use of AI while driving business outcomes and customer value.

The Product Counsel Senior Director provides legal counsel on product development and AI, manages IP portfolios, oversees compliance, and advises on technology transactions.

Lead a team of advanced product analysts, conduct data analysis and statistical modeling, design experiments, and develop reporting tools to drive product decisions and business performance.

Lead federal sales engineering efforts: deliver tailored demos, respond to federal RFPs/RFIs, navigate agency security reviews and ATO processes, produce solution designs aligned to federal frameworks (FedRAMP, NIST), and advise product/GT M strategy for federal use cases in fraud, identity, and AML.

Provide commercial legal support across Sales, Product, Partnerships, Procurement, and Engineering: draft and negotiate NDAs, SaaS and vendor agreements, advise on product and privacy/regulatory risks (GDPR, CCPA/CPRA, GLBA), improve contract lifecycle management, and respond to day-to-day legal inquiries and ad hoc projects.

Support development of pricing arrangements, financial models, budgets and AFAs for a law firm. Produce pricing analyses, competitive market research, and performance metrics. Collaborate with attorneys, IT, and data teams to implement pricing tools (Elite 3E, Iridium), leverage AI/analytics for forecasting, and train stakeholders on pricing technology.

Lead and grow the AI Forward Deployed Engineering team, oversee customer AI/ML transformations, and develop strategic partnerships while managing key accounts.

Develop and scale reinforcement-learning systems that close the loop between automated labs and reward models. Build synthetic data engines and inference infrastructure for large-scale training, maintain evaluations of learned policies using proprietary experimental datasets, and address real-world challenges like experimental noise and expensive queries.

As a Senior Machine Learning Engineer, you'll design and develop infrastructure and models for AI-powered applications while collaborating with teams to enhance product functionality.

As a Senior Staff Machine Learning Engineer, you will lead the development and deployment of machine learning models, ensuring they drive business growth and meet performance requirements. You will collaborate with teams, manage data pipelines, and implement state-of-the-art solutions while continuously improving model performance.

The role involves developing and deploying machine learning models for forecasting within the Camus platform, requiring collaboration and technical depth in ML.

Lead design, training, fine-tuning, evaluation, and production deployment of TTS/voice-generation models. Translate research into reliable, low-latency production systems, define ML best practices, and collaborate across research, engineering, and product to drive execution.

Design and develop AI capabilities and scalable microservices. Collaborate to integrate AI models and ensure performance in cloud environments.

As an MLOps/ML Platform Engineer, you will build and manage ML systems, optimize workloads, and ensure production model reliability while collaborating across teams.

Seeking a Senior Machine Learning Engineer to design and implement ML systems, optimize deployment, and collaborate with data teams, focusing on scalability and performance.