Top Senior Machine Learning Jobs in Atlanta, GA

Design and build infrastructure for ML model training and deployment. Collaborate with teams and monitor performance using AWS tools. Focus on reliability and efficiency in high-availability environments.

The Solutions Engineer will drive the adoption of AI-powered solutions in the electric utility sector, providing technical consulting and customer enablement. Responsibilities include gathering requirements, architecting solutions, leading RFI/RFP processes, and delivering training. Extensive travel is required for client engagement.

As an AI/ML Ops Engineer, you will architect and operate ML pipelines, automate CI/CD processes, and collaborate with cross-functional teams to enhance engineering productivity.

The role involves designing scalable AI solutions, managing large-scale AI deployments, building client relationships, and delivering presentations. Requires experience in MLOps and knowledge of ML ecosystems.

The Machine Learning Engineer will enhance search retrieval, train ranking models, build query understanding systems, and ensure robust pipelines for Reddit's AI-driven products.

As a ML Engineer focused on inference, you'll design and optimize deep learning models for real-time communication AI applications, collaborating with cross-functional teams and ensuring production readiness.

Design and maintain scalable machine learning infrastructure, collaborating with data scientists, ensuring performance, security, and compliance of AI systems.

As a Senior Machine Learning Engineer, you'll develop and deploy scalable ML models, collaborate with teams, and drive data-driven insights for enhanced user experiences.

Lead the backend engineering team for Runway's machine learning platform, focusing on building infrastructure, monitoring, and scaling production processes.

The Principal Machine Learning Engineer will develop ML solutions using advanced models, collaborate with teams, and leverage cloud resources for applying ML products at scale.

The Software Engineer III role involves designing and developing AI tools, mentoring teammates, and ensuring software meets compliance and integration needs while leveraging generative AI techniques.

The Senior Software Engineer will develop and maintain foundational ML infrastructure for feature computing, storage, and retrieval, impacting numerous teams at Reddit.

The Senior Product Manager will lead the strategy and execution of AI-driven features in a SaaS platform, ensuring high-quality user experiences and data-driven decisions while mentoring junior team members.

Develop and optimize large-scale ML models and training pipelines for automating PCB layouts, collaborating on data pipeline design and novel architectures.

As a Senior ML Ops Engineer, you'll build ML infrastructure, implement automated deployment, optimize model serving, and ensure production performance.

The Senior AI/ML Engineer will design and maintain scalable ML infrastructure, mentor data scientists, and ensure production readiness of AI models.

Design and deploy machine learning models for autonomous vehicles, focusing on data tagging, dataset curation, and model validation.

The Engineering Manager - Data & ML will redesign and scale Underdog's data and ML platform, establishing best practices, leading a team, and collaborating with cross-functional teams to optimize data systems.

Lead the development of AI agents and infrastructure, collaborate with stakeholders, design APIs and SDKs, and advocate for best practices.

The Solutions Architect for AI/ML at Snowflake will advise clients on best practices for Data Science workloads, design solutions, and build ML pipelines. Responsibilities also include working hands-on with SQL and Python, maintaining technical expertise and collaborating with teams to improve products.

The Senior Machine Learning Engineer will develop scalable ML systems, lead a team, mentor juniors, and work cross-functionally to enhance customer experience through machine learning solutions.

Lead the design, development, and implementation of machine learning products, creating data pipelines and maintaining production stability.

Lead the design and optimization of ML systems at Scribd, managing cross-team projects, mentoring engineers, and shaping technical direction for ML initiatives.

Design and optimize machine learning systems, build scalable data pipelines, and run experiments to improve recommendations for Scribd's products.

Join Equilibrium Energy as a Staff/Sr Staff Software Engineer to enhance the Science Platform for ML model deployment, requiring strong Python and ML expertise.