Top Machine Learning Jobs in Atlanta, GA

As a Senior Machine Learning Engineer at Splice, you will design and optimize advanced generative models for audio applications, collaborate with researchers and engineers to deploy machine learning models, and stay updated with advancements in relevant fields. Your role encompasses performance evaluation, documentation, and knowledge sharing within a passionate team committed to AI in music production.

The Staff/Senior Machine Learning Engineer will lead ML projects, design and implement end-to-end ML solutions, optimize models, and analyze security data within a collaborative team environment, contributing to cybersecurity technologies.

As a Principal Solutions Architect, you will design and implement data solutions tailored to client needs, drive account growth, provide thought leadership, and ensure quality in solutions. Your role involves working closely with data scientists, creating effective data environments, and leading consulting engagements to drive client success.

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 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 Machine Learning Engineer specializing in Infrastructure and Operations, you will optimize and scale AI systems, deploy ML models, and ensure data security and compliance while maintaining a robust infrastructure. You'll collaborate with data scientists, implement automated workflows, and troubleshoot infrastructure-related issues.

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.

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.

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 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 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.

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.

The Staff Machine Learning Engineer will develop and maintain ML-driven products, focusing on fine-tuning LLMs, deploying models on GPUs, and addressing product-related ML challenges in a dynamic environment. Responsibilities include building training pipelines, managing customer issues, and integrating advancements in generative AI.

The Principal Machine Learning Engineer will lead the AI team in developing innovative ML models and algorithms, optimizing solutions, and mentoring engineers. Responsibilities include troubleshooting model issues, creating pipelines for LLM tuning, collaborating on product innovation, and integrating the latest AI advancements into systems.

The Senior Machine Learning Engineer will build and maintain training pipelines for fine-tuning LLMs, serve and deploy models on GPUs, and formulate solutions to novel product issues. The role involves addressing customer issues related to ML performance and keeping abreast of developments in generative AI.

As a Senior Machine Learning Engineer, you will transform and deploy machine learning models from prototype to production, optimize for performance and scalability, and ensure model reliability through monitoring and retraining. You will collaborate with cross-functional teams to innovate and maintain ML solutions in a cloud environment.

As a Machine Learning Engineer at EDO, you will improve modeling pipelines for the Ad EnGage product by identifying and resolving performance bottlenecks in Snowflake queries and Python code, optimizing data processing operations, and developing profiling test suites for better efficiency in modeling.