Top Senior Machine Learning Jobs in Greensboro, NC

The AI Strategist leads AI initiative ideation and planning, collaborates across departments to define use cases, and ensures alignment with strategic and regulatory goals.

As a Senior AI Engineer, you will develop and optimize Generative AI applications, manage AI pipelines, collaborate with clients, and ensure production delivery with MLOps best practices.

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

The Sales Engineer will serve as a technical lead, guiding clients on advanced data integration and analytics solutions in healthcare, impacting revenue and client engagement.

As a Staff Product Manager for Ads Optimization, you will define strategies for campaign performance, collaborate with engineering and data teams, and present insights to leadership, focusing on optimization and automation.

Seeking a Senior Data Scientist to develop AI/ML models for predictive maintenance and logistics forecasting, ensuring alignment with mission objectives and collaborating within Agile teams.

The Senior ML Engineer will architect ML infrastructure, deploy models, manage data, ensure MLOps practices, and collaborate on data projects with diverse teams.

Lead and manage a team developing ML models for self-driving vehicles, define motion planning projects, and collaborate with cross-functional teams to enhance performance.

Lead the development of advanced perception algorithms for self-driving vehicles. Collaborate and mentor engineers, optimize algorithms, and implement sensor fusion for robust perception systems.

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

As a Senior ML Engineer, you will lead the design and operation of GenAI solutions, focusing on LLM development and deployment, mentoring colleagues, and collaborating with cross-functional teams to enhance AI capabilities for the insurance sector.

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.

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.

Serve as an AI/ML-focused solution engineer for Healthcare & Life Sciences: provide technical guidance, design cloud data and lakehouse architectures on Snowflake, lead demos and proofs-of-concept, support sales cycles, collaborate with product and engineering, and communicate AI/ML value to technical and executive stakeholders.

Build and design backend services, AI agents, and machine learning models. Collaborate cross-functionally to deliver AI features and maintain code quality.

The Senior ML Data Scientist will develop machine learning models to detect fraud, manage the data science lifecycle, and collaborate with teams on strategies.

Build and improve machine learning models and systems to classify and enrich Internet data, collaborating with engineering, research, and product teams.

As a Staff Data Scientist, you will lead initiatives to build and optimize machine learning models, collaborate across departments, and solve complex business problems using data.

Lead the development and implementation of machine learning models for energy trading optimization and forecasting, while overseeing a team of data scientists and engineers.

The role involves building bioinformatics and ML pipelines, analyzing multi-omics data, mentoring, and collaborating across teams to develop actionable insights and scientific breakthroughs.

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.

The role involves improving AI agent quality through designing experiments, maintaining evaluation infrastructure, optimizing LLM inference, and collaborating with product teams. Responsibilities include end-to-end ownership from research to deployment in a dedicated ML Engineer context.

The Senior Machine Learning Engineer will design and operate advanced ML systems for immersive experiences, enhance workflows, and lead projects while mentoring peers.

The Machine Learning Engineer will design and build systems that improve the AI shopping agent by using real user feedback, focusing on feedback loops and metrics to enhance user interactions and agent performance.