Top Machine Learning Jobs in Atlanta, GA

Develop and optimize ML pipelines, fine-tune language models, and implement MLOps practices while collaborating with SMEs and product managers.

The Senior Product Marketing Manager will drive messaging, positioning, and go-to-market strategy for the Manhattan Active Platform, translating technical capabilities into business benefits and developing narratives that highlight technological innovations.

As a Staff Software Engineer, you'll develop and maintain backend and pipeline systems for search and recommendation services on Reddit, focusing on low-latency, scalable model-serving APIs.

Lead a team of data scientists developing ML-driven products, managing infrastructure, training models, and ensuring production quality while collaborating with senior leadership.

The AI/ML Engineer will architect, maintain data pipelines, develop AI applications, and optimize distributed systems for fraud detection and prevention.

Implement and optimize production-ready analytics code, maintain Python repositories, research data sources, build predictive models, and collaborate with teams.

This internship focuses on clinical pharmacology and AI/ML modeling, providing experience in developing predictive models using clinical datasets.

As a Senior Machine Learning Engineer, develop infrastructure for ML model deployment, collaborate with teams, and ensure model reliability and performance.

Lead product marketing initiatives at Viaduct, creating compelling content, partnering with sales and product teams, and driving demand in the automotive sector.

As a Principal ML Architect, lead technical strategy and client engagements, mentor ML engineers, and oversee project lifecycle in delivering complex AI systems.

As a Junior AI/ML Engineer, you will work on generative AI applications, traditional ML projects, and MLOps, under the mentorship of senior engineers.

As a Senior Consultant II, you will integrate AI technologies into business applications, build scalable microservices, and deploy AI models in production environments.

Work with the product team on automating data ETL pipelines, deploying ML models, and connecting ML models to user interfaces. Collaborate with cross-functional teams on product development.

Lead a team of ML Engineers to develop technology for healthcare, emphasizing hiring talent, technical leadership, and collaboration with stakeholders.

Research and develop algorithms and models for multimedia content creation. Collaborate across teams to innovate in computer vision and generative models.

The Machine Learning Scientist will design and evaluate algorithms for media processing, collaborate with cross-functional teams, and expand expertise in computer vision and related fields.

The Senior Solution Innovation Architect will design and implement AI/ML solutions on the Snowflake platform, collaborate with customers, and provide technical expertise in ML and AI applications.

The role involves designing, developing, and deploying ML models, collaborating with cross-functional teams, and improving model performance through testing and experimentation.

Design and implement machine learning perception systems for autonomous ground vehicles. Work on deep learning models, optimize for edge devices, and collaborate across teams.

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.