Top Machine Learning Jobs in Atlanta, GA

The role involves sourcing and recruiting senior engineers in AI, ML, and related fields, building talent pipelines, and collaborating with engineering leadership.

Develop custom models and algorithms for large datasets, collaborate with stakeholders to leverage data for business decisions, and assess data sources and techniques.

The role involves developing scalable ML solutions, leading cross-functional discussions, analyzing knowledge data, and producing technical documentation to improve search relevance using AI and machine learning technologies.

Lead the design and implementation of deep learning models for biological data, focusing on model architecture, project leadership, and innovation in machine learning applications in biology.

Design and implement software solutions for machine learning operations, focusing on geospatial imagery analytics and MLOps software development.

The Machine Learning Engineer III will design, develop, and deploy machine learning models and algorithms, mentor junior staff, and collaborate with cross-functional teams to solve complex business problems.

As a Machine Learning Engineer, you'll optimize and deploy production ML models, build inference services, and collaborate closely with teams to integrate new models and enhance performance.

Design and build recommendation and personalization systems, conduct A/B testing and causal inference, and mentor the data team in best practices.

The Applied ML Engineer at Ideogram will turn generative models into production features, collaborate with teams to define metrics, and ensure ML systems' reliability.

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

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

The Senior Machine Learning Engineer will design and maintain ML solutions for fraud detection, collaborating across teams and establishing MLOps best practices.

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

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

Develop and optimize machine learning models for processing financial documents, mentor junior staff, and collaborate across teams to enhance software products.

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.

A Machine Learning Engineer will design and optimize AI components, develop datasets, evaluate models, and collaborate cross-functionally to enhance AI insights.

As a Senior Software Engineer in Machine Learning, you'll develop and maintain machine learning models for geospatial analytics, collaborate with teams to refine algorithms, and ensure high-quality deployment of models at scale.

Design and implement machine learning models and algorithms for AI/NLP-driven services while collaborating with teams for optimization and efficiency.

You will take ownership of ML Ops systems, improve CI/CD processes, and enhance software infrastructure for ML Engineers providing real-time intelligence products.

The role involves developing advanced machine learning solutions, collaborating with experts, and managing ML model architecture and deployment.

The Senior Staff AI/ML Engineer will design, develop, and deploy scalable machine learning models, collaborating with teams to address business challenges and ensure high performance in production environments.

Develop AI tools using statistical modeling and establish pipelines for causal inference and predictive analytics to assist political campaigns.

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 Machine Learning Engineer will design, train, and evaluate computer vision models, collaborate on engineering improvements, and deploy ML systems for surgical workflows.