Top Machine Learning Jobs in Atlanta, GA

The Applied Machine Learning Engineer will develop AI-driven solutions, focusing on backend systems, AI integration, model deployment, and MLOps best practices, while collaborating with cross-functional teams.

The role involves designing and implementing cloud-native infrastructure for AI/ML workloads, optimizing Kubernetes environments, and contributing to open-source MLOps tooling.

As a Senior ML/AI Platform Engineer, you will design and productionize scalable AI/ML models, mentor junior engineers, and collaborate with cross-functional teams to optimize machine learning pipelines.

The Lead Machine Learning Scientist designs and develops ML solutions, leads project teams, mentors members, and collaborates with clients to solve complex problems.

As a Staff Machine Learning Engineer, you will design scalable ML systems, mentor engineers, solve complex problems, and optimize models in a fintech environment.

As a Machine Learning Engineer, you'll develop datasets and pipelines for navigation applications, work with geospatial data, build ML models, and ensure data quality.

The Forward Deployed ML Engineer will integrate AI/ML models into clinical software, assist in model fine-tuning, and engage with clients to ensure success in healthcare deployments.

As a Machine Learning Engineer, you'll innovate features for dataset curation, model analysis, and integrations, focusing on Visual AI and open-source contributions.

Seeking a Senior Machine Learning Engineer to design and implement ML systems, optimize deployment, and collaborate with data teams, focusing on scalability and performance.

As a Principal Solutions Architect, you will architect AI/ML solutions, lead teams, engage clients, and drive account growth while ensuring delivery excellence.

As a Machine Learning Engineer, you'll build and deploy ML systems, optimize models for production, and collaborate on data processing and monitoring, while enhancing your software development skills.

The AI/ML Engineer will develop, deploy, and optimize machine learning models for grid stability and interconnection predictions, integrating data from various sources and collaborating with engineers.

The role involves designing, optimizing, and deploying large-scale ML/AI automation systems, ensuring service availability and cost efficiency through architectural best practices.

As a Machine Learning Engineer at Shipwell, you'll build and scale AI-powered logistics solutions, maintaining data pipelines and ML infrastructure across the organization.

Lead architectural vision and development of scalable infrastructure for self-driving technology, mentoring engineers and overseeing complex projects.

Design and build ML infrastructure components for autonomous vehicles, ensuring scalability and robustness for high-volume data processing and model training.

The role involves developing advanced multimodal customer experiences using AI, mentoring others, and refining AI processes for Zillow's platforms.

The role involves designing and operating modern data and ML platforms, building scalable pipelines, implementing MLOps systems, ensuring compliance, and enabling AI solutions in public health.

The Senior Software Engineer II at Aledade will develop scalable AI/ML solutions, mentor junior engineers, and collaborate with cross-functional teams in the healthcare industry.

The Machine Learning Engineer will develop software solutions, optimize data pipelines, and deploy machine learning models using cloud platforms and best practices.

As an ML Solutions Architect, design, implement, and lead machine learning solutions for Conversation AI, collaborating with cross-functional teams to address complex business challenges.

The Principal Software Engineer will design and deliver backend systems and APIs for AI features, focusing on integration of Java and Python capabilities while ensuring code quality and mentoring team members.

The Machine Learning Engineer will work on AI/ML projects, optimizing data systems, supporting cloud migrations, and delivering predictive insights using AWS services.

The position involves driving AI/ML product development for personalized experiences, partnering across teams, and launching impactful products.

As a Senior Geospatial Machine Learning Engineer, you will develop and improve algorithms for vegetation analysis, enhance existing products, and lead projects impacting wildfire risk management.