Top Machine Learning Jobs in Atlanta, GA

The Principal Software Engineer, ML at Relyance AI will lead initiatives in ML and NLP for information extraction and AI backend projects. Responsibilities include strategizing, designing, and executing ML solutions, collaborating with cross-functional teams, and working with advanced models such as GPT-4 and BERT.

The Machine Learning Architect will design and execute machine learning projects from proof-of-concept to deployment, architecting solutions on cloud platforms such as AWS, GCP, and Azure. The role involves collaborating with business representatives, managing all project phases, and ensuring technical excellence in machine learning delivery while staying current with advancements in the field.

The Senior Software Engineer for ML Infrastructure will design and refine MLOps workflows, manage model deployment and versioning, and ensure reliability and scalability of geospatial ML products. Responsibilities include building CI/CD pipelines, integrating external ML models, and collaborating with data scientists to operationalize ML systems.

As a Senior Technical Product Manager, you will oversee the development of products and processes for evaluating machine learning models, ensuring quality, accuracy, and ethical implementation. You will manage QA strategies, data quality, and automate testing frameworks while collaborating closely with engineering teams to improve model performance and report findings.

The AI/ML Software Engineer will design, develop, and deploy AI/ML models and applications focused on geospatial data, optimizing model performance and implementing MLOps practices. Responsibilities include processing geospatial datasets, collaborating with cross-functional teams, conducting model evaluations, and ensuring compliance with security best practices.

As a Senior Machine Learning Engineer at Reserv, you will develop AI models and machine learning solutions, mentor junior data scientists, and collaborate with cross-functional teams to address operational inefficiencies. You will design scalable architectures and ensure high-quality code delivery.

As a Machine Learning Engineer, you will develop applied ML models and manage end-to-end pipelines to deliver insights for key clients. Responsibilities include training deep learning models on private datasets, conducting experiments, feature engineering, and collaborating with interdisciplinary teams for effective decision-making.

As a Machine Learning Engineer at Corelight, you will develop and implement scalable ML solutions for network security, collaborating with data scientists and security experts. You will engage in all stages of AI/ML projects, from exploration to productization, focusing on ML pipelines, strategies to deploy LLMs, and ensuring model quality.

As a Machine Learning Engineer specializing in natural language processing at Entefy, you will use deep learning and various methodologies to develop innovative algorithms that enhance communication technologies. Your responsibilities will include working on confidential high-impact projects and applying your knowledge in machine learning theory and text analytics.

The Sr. Manager of ML Production Engineering leads the ML Production Engineering function, managing the engineering team responsible for Matterport’s 3D reconstruction pipeline. It involves optimizing ML Ops and Dev Ops, collaborating on designing and implementing ML pipelines, and overseeing the integration of ML models into applications.

As a Lead Machine Learning Infrastructure Engineer, you will design, develop, and maintain scalable infrastructure supporting ML models, optimize distributed systems, and collaborate with teams to enhance ML workflows. Your role includes mentoring junior engineers and integrating new ML infrastructure advancements.

As a Senior Software Engineer, you'll build and maintain foundational ML infrastructure at Reddit, enabling feature computation and retrieval for various applications. Responsibilities include mentoring team members, working with management on project execution, and advancing the ML Platform collaboratively with other engineers.

The Senior Machine Learning Engineer will develop and implement advanced machine learning models to enhance HubSpot's Unstructured Data Platform. Responsibilities include improving model performance, communicating technical concepts, and collaborating with cross-functional teams to ensure successful model integration across various product features.

As a Software Engineer at Waabi, you will build tools and pipelines to enhance AI-driven self-driving technology, collaborating with a team of experts on dataset curation, training, and model evaluation, while ensuring high-quality code and project delivery.

The Senior Machine Learning Engineer at Path Robotics will develop advanced robotic learning algorithms, implement computer vision solutions, train and optimize large-scale models, and collaborate with teams. This role involves mentoring, conducting research, and contributing to publications.

The Staff Machine Learning Engineer will lead the development and optimization of Large Language Models and Mixture of Experts models, collaborating with cross-functional teams and conducting research to improve performance and efficiency. The role also involves mentoring junior engineers and staying updated with advancements in AI.

As an ML Solutions Architect, you will design and implement machine learning solutions for the Conversation AI platform. Your role includes developing scalable ML architectures, end-to-end ML pipelines, and integrating the latest advancements in ML technologies. You will collaborate with cross-functional teams to address business challenges and drive innovative solutions.