Top Remote Machine Learning Jobs in Greensboro, NC

Lead marketing data science efforts, overseeing analytics and machine learning strategies to enhance user acquisition, engagement, and retention. Mentor a team and communicate data insights to executives to influence marketing and budget decisions.

Lead the development and execution of ML-driven User Acquisition products, improving advertiser experience and managing product roadmaps in a fast-paced environment.

The Engineering Manager will lead teams in developing and managing Blackbaud's Data & AI platform, focusing on scalability, security, and cost-efficiency.

The DS&ML Group Product Manager oversees Data Science and Machine Learning capabilities, defining strategic vision, managing product portfolios, and ensuring delivery aligned with business needs. Responsibilities include developing roadmaps, executing models, scaling functionalities, and mentoring a team.

The Partner Enablement Technical Lead will design and manage technical learning programs for partners, focusing on Data & AI technologies, and align strategies with business needs to enhance partner proficiency.

Manage technical programs for generative AI video models, translating research into milestones, coordinating teams, and ensuring successful execution across all phases.

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

As a Staff Machine Learning Engineer, you will develop, productionize, and deploy ML models for clinical use, ensuring real-world effectiveness through hands-on coding and infrastructure building.

The role involves improving machine learning ranking models, implementing algorithms, and taking full ownership of machine learning systems within Quora's product.

The ML Engineer will leverage deep learning for natural language processing tasks, impacting Entefy's products while requiring strong machine learning fundamentals and NLP expertise.

The Staff Machine Learning Engineer will develop and maintain MLOps tools, optimize model performance, and collaborate on ML system architecture with a focus on enhancing developer experience.

The Enterprise Account Executive will drive revenue by engaging with enterprise insurance clients, managing the sales cycle, and fostering strategic relationships with executives, leveraging Vellum's data analytics platform.

As Director of AI/ML, lead the ML organization, set technical vision, mentor a high-performing team, and contribute to model development and production deployment.

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.

As a Staff Machine Learning Engineer, you will optimize Quora's ad products by applying machine learning algorithms, taking ownership of systems, and collaborating across teams.

Lead the Applied ML team's experimentation efforts, mentoring scientists and engineers to improve AI-driven methodologies and collaboration across various product areas.

As a Senior MLOps Engineer, you will manage production ML systems, define lifecycle strategies, optimize ML pipelines, and collaborate with cross-functional teams to enhance ML operations.

You will lead technical strategy and engineering for ML-powered messaging features at Airbnb, integrating solutions and collaborating with teams to enhance user communication. Responsibilities include system design, mentoring, and establishing engineering standards.

The AI Forward Deployed Engineer designs and implements AI solutions, collaborating with stakeholders, enhancing reliability, and producing reusable resources. Responsibilities include diagnosing AI solution issues and engaging with finance and data teams.

Design and build machine learning models for Zillow's product features, optimize AI components, and mentor engineers within a cross-functional team.

As a Senior Machine Learning Engineer, you will design and train ML models for logistics, manage their production deployment, and optimize their performance while collaborating with the data science team.

As a Machine Learning Engineer, you will design and build AI capabilities, develop scalable ML infrastructure, and collaborate on production systems in the real estate domain.

Lead architecture and engineering for production-grade ML in healthcare: design MLOps CI/CD, scalable low-latency inference for LLMs and classical models, build reliable data pipelines for FHIR/HL7/DICOM, manage cloud IaC and observability, ensure HIPAA/HITRUST compliance, and mentor engineering teams to operationalize agentic AI workflows.

The Senior ML Engineer will design evaluations for AI features, optimize pipelines, and ensure quality in ML systems while collaborating with cross-functional teams.

The role involves deploying and optimizing AI/ML models, integrating them into products, building APIs, and ensuring reliability through testing and monitoring. Candidates will work in a collaborative environment to enhance their MLOps and software skills.