Top Machine Learning Jobs in Raleigh, NC

Design and implement backend ML systems for personalized feeds at Reddit. Mentor teams, drive technical discussions, and improve MLOps tools.

Lead the design and development of machine learning infrastructure for robotics, defining strategies, collaborating with teams, and ensuring best practices in MLOps.

As a Principal ML Engineer, you will design ML architecture, tackle technical challenges, mentor engineers, and influence ML strategy across the company.

The ML Scientist will lead data science and ML projects, automate reporting, support product development, and maintain ML infrastructure at Harvard Business Publishing.

Develop and support ML infrastructure for large-scale scientific workflows, improve automation processes, and contribute to product features in AI-enabled drug discovery.

As an ML Ops Engineer, you'll optimize and deploy AI models, ensure high performance, and collaborate with teams for scalable solutions.

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.

Lead high-impact machine learning projects, developing systems for advertising optimization, collaborating cross-functionally, and implementing statistical techniques.

The Sr. Staff Machine Learning Engineer will lead architecture and development of ML systems, enhance patient interactions, optimize treatment recommendations, and mentor engineers.

The role involves designing and maintaining ML infrastructure, ensuring performance and security, collaborating with ML engineers, and implementing modern AI capabilities.

Lead the Safety ML team at Discord, developing AI/ML infrastructure, collaborating on safety challenges, and mentoring engineers while driving technical strategy and innovation.

As a Senior Data Scientist, you will collaborate across teams to enhance data science, analyze models, and improve product features to aid student writing.

Lead the development of data science solutions for inventory and logistics planning, optimize planning processes, and deploy predictive models. Collaborate across functions and present insights to stakeholders.

The role involves developing cloud solutions and enhancing ML/AI pipelines, ensuring service availability, and automating deployments in a scalable environment.

Explore AI/ML technologies, design and integrate models, build prototypes, and collaborate with a cross-functional team to develop novel AI features.

Lead the design and deployment of scalable ML systems, mentor engineers, and collaborate on impactful ML solutions in production environments.

The Software Engineer (Full Stack) will develop and deploy clinical AI/ML products, ensuring product quality and collaborating with cross-functional teams.

Lead the design and deployment of scalable ML infrastructure, focusing on MLOps and LLM strategies, while mentoring team members and ensuring operational maturity.

The Staff Machine Learning Engineer will lead ML initiatives, develop and deploy models, mentor other engineers, and align efforts with business goals to drive growth at Niche.

As a Lead AI/ML DevOps Engineer, you will oversee AI/ML model development and deployment, enhance CI/CD processes, and mentor a DevOps team.

The Senior ML Solutions Architect will design and implement LLM-based AI solutions, collaborate with clients, and enhance the Nebius platform.

As a Lead Machine Learning Engineer, design and maintain scalable ML solutions, optimize workflows, evaluate model performance, and collaborate with cross-functional teams to integrate complex data-driven applications, ensuring high reliability and performance standards.

As a Senior Machine Learning Engineer, you will build and productionize ML models, develop scalable infrastructure, and mentor teams to optimize marketing products.

As a Software Engineer, you will enhance Machinify's AI/ML systems for healthcare claims processing by building robust data science solutions and collaborating closely with data scientists.

Responsible for developing and maintaining Machine Learning pipelines. Lead projects, mentor team members, and collaborate across teams.