Top Remote Machine Learning Jobs in Atlanta, GA

The Principal AI/ML Platform Engineer leads the development and delivery of ML and GenAI platforms, ensuring scalability, compliance, and performance across various workflows and products, while mentoring the engineering team.

This role involves developing and integrating AI/ML models within GCP using Python, optimizing LLM performance, and applying MLOps practices. Strong collaboration with architects is required for implementation and analysis of workflows.

Lead efforts in building and maintaining ML platforms, improve metrics pipelines, and manage data collection for perception systems. Collaborate with cross-functional teams and ensure workflow reproducibility and traceability.

As a Senior Machine Learning Engineer, you will design and train ML models for logistics, manage their production deployment, and optimize their performance while collaborating with the data science team.

The Senior ML/AI Engineer designs and implements ML/AI solutions, leading end-to-end ML/AI pipelines, collaborating with teams, mentoring, and developing infrastructure for large-scale data-driven products.

Lead research and development of advanced fraud detection ML models, experiment design, productionizing prototypes, and mentoring engineers.

The role involves improving recommendation systems using machine learning, developing end-to-end ML systems, and collaborating with engineers.

The Data Scientist will develop machine learning models to optimize software build processes, analyzing large datasets and collaborating with teams for improvements.

The Senior Product Manager will develop AI tools, collaborating with research, engineering, and design to meet user needs and drive business value.

The Senior Machine Learning Engineer at SmarterDx will deploy, maintain, and optimize machine learning models, collaborating across disciplines to integrate these solutions and improve clinical AI outcomes.

The Senior Software Engineer will design and build infrastructure for ML model training and deployment, focusing on AWS technologies, reliability, and collaboration with ML teams.

The Machine Learning Solutions Architect designs and implements data solutions, overseeing model deployment and ensuring robust performance and integration within customer environments.

The role involves automating and maintaining AWS infrastructure, collaborating with engineering teams for deployment, optimizing ML infrastructure, and ensuring compliance and security standards in a cloud-native environment.

The role involves building deep learning models for ad candidate retrieval and ranking, improving recommendation systems, and taking ownership of ML systems.

As a Machine Learning Customer Success Engineer, you will facilitate ML workflows, manage user relationships, and contribute to FiftyOne's development.

The Principal AI/ML Engineer will lead the design, implementation, and deployment of AI systems, mentor junior engineers, and ensure model performance and reliability in production environments.

Lead the design and implementation of ML infrastructure, working on the model lifecycle, collaborating with researchers and engineering teams, and ensuring robust AI systems.

As an AI Specialist SC, you will support major global clients by offering presales machine learning solutions, driving business transformations and technical discussions, while collaborating across teams.

Lead architecture and engineering for production-grade ML in healthcare: design MLOps CI/CD, scalable low-latency inference for LLMs and classical models, build reliable data pipelines for FHIR/HL7/DICOM, manage cloud IaC and observability, ensure HIPAA/HITRUST compliance, and mentor engineering teams to operationalize agentic AI workflows.

The Senior Principal AI/ML Architect will drive AI architectural vision, influence multi-squad strategy, design intelligent systems, and set operational standards for Yahoo Mail's AI capabilities.

As a Machine Learning Engineering Intern at Airbnb, you will drive an AI-focused project, collaborate across teams, and contribute to search relevance and personalization initiatives.

The Machine Learning Engineer will design, build, and maintain scalable ML systems, optimize ML pipelines, implement MLOps, and collaborate with teams to deploy models into real-time products.

The AI / ML Solutions Engineer will implement and scale machine learning workloads using Ray, advise customers on ML architecture, and enable MLOps teams through technical guidance and support.

The Senior Machine Learning Engineer will manage the lifecycle of ML models, transform prototypes to production code, build training pipelines, and monitor system performance.

As a Senior Machine Learning Engineer, you will develop and deploy AI-driven products to enhance clinical trials, collaborating with teams to improve patient care through scalable machine learning solutions.