Top Machine Learning Jobs in Atlanta, GA

As a Staff Machine Learning Engineer at Fakespot, you will leverage AI and machine learning techniques to analyze unstructured data, develop and optimize models for tasks like entity recognition and text generation, and collaborate with cross-functional teams. You'll also monitor and refine models for performance, ensuring the delivery of trustworthy tools to enhance eCommerce transparency.

In this role, you will apply statistical and machine learning techniques to analyze unstructured data, develop and fine-tune machine learning models, utilize pretrained language models, and ensure their effectiveness in production. You will work collaboratively with interdisciplinary teams to enhance product features while staying updated with advancements in NLP.

As a Machine Learning Engineering Intern at Symbl.ai, you will collaborate on the Nebula LLM, develop machine learning algorithms, and tackle real-world challenges in language technology while gaining practical experience.

As a Senior ML Infrastructure Engineer, you will design and maintain ML pipelines, implement CI/CD processes, and manage production infrastructure for machine learning models. You will work collaboratively with data scientists and engineers to ensure seamless integration of models, optimize performance, and automate data management, all while ensuring scalability and reliability of the infrastructure.

As the Data Science/Machine Learning Director at AlixPartners, you'll lead the design and execution of advanced data workflows, statistical models, and visualizations. You will interact with top-level executives, tackle high-impact projects, and manage data migration and analysis, while building ETL processes and ensuring data quality and integrity.

As a Staff Data Scientist in Growth, you'll develop predictive models and analytics to enhance customer insights and optimize marketing strategies. Collaborate with teams to integrate data-driven findings into decision-making, and lead experiments to validate growth hypotheses. Your role is critical in driving customer engagement and contributing to overall growth initiatives at Quince.

The ML Engineer - Inference at Symbl.ai will develop and optimize deep learning models for real-time communication applications, focusing on the Nebula language model. Responsibilities include designing algorithms, integrating models into production, optimizing for various environments, and evaluating model performance, all while collaborating with cross-functional teams.

As a Research Intern at Symbl.ai, you will engage in transformative AI/ML research projects, working with real-world data and deploying ML techniques. Your responsibilities include contributing to the development of the Nebula LLM, analyzing data, and collaborating with experienced researchers and developers.

As a Senior Machine Learning Engineer, you will develop and optimize machine learning systems, focusing on model training, pipeline development, and fine-tuning large language models to meet business needs. You will work collaboratively with product teams, mentor junior staff, and keep abreast of advancements in the field to enhance the company's ML offerings.

Seeking an Engineering Manager for the Cloud Data Engineering Practice at Caylent. Responsibilities include acting as a data engineering SME, managing a team of Architects and Engineers, overseeing data delivery engagements, and providing technical guidance. Qualifications include strong experience in AWS data landscape, expertise in Cloud Data Engineering areas, and excellent communication skills.

As a Senior Machine Learning Engineer at Nomad Health, you will lead end-to-end machine learning projects, creating models that address critical business challenges. Responsibilities include designing and delivering ML models, maintaining production models, and leveraging cloud-based technologies.

As a Back-End Software Engineer, you will lead the development of AI solutions and integrate data processing pipelines while collaborating closely with teams to enhance chatbot functionality and optimize system architecture.

As a Machine Learning Engineer at CoLab, you will develop and deploy machine learning models, optimize features, and ensure models are production-ready. You will lead experiments, automate data pipelines, and collaborate with cross-functional teams to integrate ML solutions. Your role is pivotal in driving insights, improving data processing, and maintaining model performance in a fast-paced SaaS environment.

The Senior ML Researcher will lead the research and development of machine learning models, architect methodologies for training and fine-tuning, evaluate model performance, and mentor team members. The role emphasizes collaboration with product teams and staying updated on ML advancements to drive innovations in model architecture and optimization.

The Staff Machine Learning Engineer will lead the development of machine learning systems, managing the end-to-end lifecycle of projects, optimizing data pipelines, and ensuring model performance in production. The role includes collaboration with cross-functional teams and leveraging cloud technologies.

The Applied Machine Learning Engineer at Anomalo will develop and enhance ML models for data quality solutions, optimize algorithms, visualize insights, engage with customers, and mentor colleagues while leading innovative projects to improve product features and user experience.

As a Machine Learning Engineer at Objective, you will develop advanced algorithms for search and recommendation technologies, experiment to optimize deep learning systems, and evaluate approaches to improve product quality. Your role involves ensuring effective machine learning deployment and driving innovation.