Top Machine Learning Jobs in Atlanta, GA

Design, implement, and maintain ML solutions using AWS SageMaker. Develop end-to-end ML pipelines and collaborate on model deployment to enhance data-driven decision-making.

Develop and optimize large-scale ML models and training pipelines for automating PCB layouts, collaborating on data pipeline design and novel architectures.

As a Senior ML Ops Engineer, you'll build ML infrastructure, implement automated deployment, optimize model serving, and ensure production performance.

As a Machine Learning Engineer, you will fine-tune transformer models, deploy machine learning solutions, and work with cross-functional teams on innovative projects.

Develop ML models and pipelines for autonomous tractor initiative, improving system safety and performance in production environments.

Leading the AI/ML team, mentoring data scientists and engineers, developing production-grade systems for cybersecurity, collaborating on architecture, and driving best practices for AI development.

The Senior AI/ML Engineer will drive AI/ML strategy, evaluate solutions, collaborate with teams, and innovate in data science.

The Senior Product Manager will lead the strategy and execution of AI-driven features in a SaaS platform, ensuring high-quality user experiences and data-driven decisions while mentoring junior team members.

As an ML Engineer, you will build and deploy machine learning models for autonomous robots, collaborating with ML scientists and engineers to enhance AI capabilities.

Lead ML projects to optimize search and recommendations at Airbnb, collaborating with cross-functional teams to enhance user experience and business impact.

Design, develop, and deploy machine learning systems, improve ML infrastructure, and partner with stakeholders to enhance data science workflows.

Develop and deploy ML models for personalization and optimization, analyze performance, and collaborate with product teams to enhance user experiences.

As a Machine Learning Engineer, you'll build scalable ML systems for personalized recommendations, collaborating with data scientists and cross-functional partners.

The role involves building scalable AI features, optimizing machine-learning pipelines, evaluating LLM outputs, and ensuring compliance with data governance standards.

The Senior Machine Learning Engineer will develop ML platforms, optimize model lifecycles, lead initiatives, and maintain code quality, collaborating with Data Science teams.

Lead the design and development of AI solutions, optimize algorithms, collaborate with teams, and develop advanced models to drive business insights.

The role involves developing and optimizing intelligent agents using large language models, collaborating with the team, and solving technical problems.

Lead the development of advanced recommendation systems and ML pipelines. Collaborate with cross-functional teams to enhance user engagement through optimization of machine learning models at scale.

The role involves building and maintaining ML pipelines, optimizing workflows, and contributing to product strategy with a focus on usability.

The Senior Full Stack Engineer will develop AI/ML features in ClickHouse Cloud, integrating databases with AI capabilities, ensuring robust API design, and building user-friendly interfaces.

As a Senior Data Engineer, you'll build a cloud-native Data Platform in Azure, design data pipelines, and collaborate with data scientists on AI/ML applications.

As a Senior Data Engineer, you'll build a data platform in Azure, design and implement data pipelines, develop cloud microservices, and mentor engineers while working with AI models.

The Principal Machine Learning Engineer will develop multimodal technologies, mentor engineers, and drive product innovation in agentic AI systems.

The Senior Product Manager will lead the strategy for an AI assistant, ensuring compliance and user satisfaction while coordinating with cross-functional teams throughout product development.

This role involves designing, developing, and scaling machine learning systems for payment flows and recommendations, leading technical initiatives, and optimizing complex financial decision systems.