Top Machine Learning Jobs in Raleigh, NC

The Senior Manager of Machine Learning Engineering will lead and mentor a team to productionize and deploy ML models, drive improvements in engineering practices, and manage projects related to machine learning and infrastructure. This role involves hands-on design and development while collaborating with cross-functional teams to meet project requirements.

The Cloud Machine Learning Engineer at Hugging Face will develop machine learning solutions leveraging cloud technologies, integrate open-source libraries with major cloud platforms, ensure model performance, and create developer experiences and APIs. Responsibilities also include writing technical documentation and engaging with the community.

The internship focuses on expanding the Hugging Face ecosystem by creating and maintaining JS/TS machine learning libraries. Responsibilities include optimizing models for in-browser inference, enabling models to run at near-native speeds, building demo applications, and fostering an open-source community.

The Machine Learning Engineer Internship at Hugging Face focuses on expanding AI tools used in Gradio, a library for machine learning demos. Interns will assist in creating a model pipeline leveraging existing Gradio spaces and prompts. Ideal candidates are passionate about open-source and have experience with modern deep learning libraries and LLMs, with a focus on user-friendly product development.

The Practice Manager leads a team in Data Science, AI, and ML, overseeing customer projects, driving successful outcomes, and mentoring team members. Responsibilities include technical leadership, project management, operational support, and fostering team culture while ensuring the overall success of the practice.

Join Pathway as a Machine Learning Researcher/Engineer focusing on foundational models. You will perform distributed model training, enhance model architectures based on research, and design new experiments. Your contributions are crucial for project success in a cutting-edge AI environment.

The Senior ML Operations Engineer at Abbott will design and develop machine learning and AI products, collaborating with data engineers and scientists to address business challenges. The role involves creating scalable ML infrastructure, customizing language models, and deploying solutions in cloud environments while mentoring team members and engaging with stakeholders to ensure effective implementations.

The Staff ML Operations Engineer will design and develop machine learning and AI systems, building scalable software solutions for big data initiatives and leading collaborations with various teams to translate business needs into AI solutions.