Top Machine Learning Jobs in Atlanta, GA

As a Machine Learning Engineer, you will create scalable machine learning systems, build reusable production data pipelines, and ensure the deployment and monitoring of machine learning models. You'll collaborate with teams to communicate findings and improve data science solutions.

The AI/ML Solution Architect will design and implement AI and machine learning features for ValGenesis products. Responsibilities include building scalable models, image processing solutions, and AI architecture, while ensuring compliance with industry regulations. The role involves collaboration with cross-functional teams and mentoring AI/ML engineers.

The Lead AI/ML Engineer will analyze business requirements and design, develop, and deploy AI solutions. Responsibilities include leading AI/ML initiatives, building end-to-end automated pipelines, researching AI technologies, and mentoring team members while ensuring ethical AI practices.

The Lead Data Scientist, ITS will develop and refine predictive models, collaborate with cross-functional teams to gather requirements, and drive data products to production. This role involves creating algorithms to solve business problems, conducting experiments to identify data anomalies, and leading projects to deliver data-driven results.

As a Software (ML Product) Engineer, you will enhance the user experience of ML tools by optimizing workflows and processes. You will collaborate with technical product managers, contribute to defining efficient ML practices, and improve DVC, an open-source tool for machine learning. A strong background in deep learning and system design is necessary to transform current workflows and engage with the ML community.

The Machine Learning Engineer at Ritual will automate Data ETL pipelines, deploy machine learning models, and develop customer-facing products. Responsibilities include scaling up model inference, connecting ML models to human interfaces, and designing large-scale data and ML pipelines while collaborating with cross-functional teams to innovate AI products.

The Group Product Manager will lead the development of innovative technologies for tvScientific's connected TV advertising platform. This role involves product strategy, market research, collaboration with cross-functional teams, and establishing key performance indicators to optimize advertising performance.

The Machine Learning Infrastructure Engineer will design and maintain scalable infrastructure for machine learning models, working alongside data scientists and engineers. Responsibilities include implementing infrastructure-as-code, deploying models efficiently, optimizing performance, and ensuring data security and integrity.