Top Machine Learning Jobs in Atlanta, GA

This role involves leading a perception team in developing algorithms for autonomous driving systems, supervising team members, and conducting research to enhance perception capabilities.

Design and implement machine learning models to solve business problems, analyze data for insights, and optimize model performance.

The VP of AI will lead NeoWork's AI strategy, ensuring adoption, developing workflows, building capabilities, and enhancing client value through AI integration.

Manage and mentor engineers, contribute to product and infrastructure, drive projects, and collaborate cross-functionally to enhance AI platforms.

The role involves defining the vision and strategy of the Outreach AI Platform, prioritizing the roadmap, collaborating with engineering and data science teams, and engaging with customers to refine AI strategies.

Lead the implementation of AI-driven supply chain solutions, collaborating with clients to enhance their business processes and ensure seamless technology integration.

Lead the development of ranking and personalization strategies for Yahoo News and Homepage, leveraging machine learning to enhance user engagement and drive monetization metrics, while managing cross-functional teams and stakeholders.

Lead end-to-end development, deployment, and improvement of production ML systems to rank claim recovery opportunities. Perform EDA, research new model architectures, implement cloud MLOps, measure business impact, and mentor teammates while owning a technical workstream.

Lead ML strategy and standards as a senior individual contributor: define ML infrastructure, tooling, and lifecycle processes; establish monitoring and feature patterns; partner across platform, data, and product teams; mentor data scientists and ML engineers to scale reliable production ML systems.

Serve as an AI/ML-focused solution engineer for Healthcare & Life Sciences: provide technical guidance, design cloud data and lakehouse architectures on Snowflake, lead demos and proofs-of-concept, support sales cycles, collaborate with product and engineering, and communicate AI/ML value to technical and executive stakeholders.

As an MLOps/ML Platform Engineer, you will build and manage ML systems, optimize workloads, and ensure production model reliability while collaborating across teams.

The Senior Product Manager will lead the strategy for an AI assistant, ensuring compliance and user satisfaction while coordinating with cross-functional teams throughout product development.

As a Software Engineer, AI/ML GenAI, you will design and implement AI features, manage embeddings, and optimize AI systems for production deployment while collaborating with product and design teams.

The role involves designing and implementing data and AI architectures, developing data pipelines, and integrating machine learning solutions while fostering Agile methodologies and collaboration.

As an AI/ML Engineer, you will design, train, and deploy machine learning models, optimize model performance, and collaborate with cross-functional teams to integrate AI capabilities into products.

The Machine Learning Engineer will work on sensing and perception algorithms, deploying computer vision algorithms, and collaborating for code testing and evaluation.

Lead research on humanistic AI for autonomous systems. Collaborate with teams, design experiments, and publish findings in top-tier publications.

Convert data science prototypes to production-grade ML tools, deploy and monitor models, run and interpret tests, manage ML platforms, identify data drift, evaluate vendor AI solutions, and communicate technical findings to varied audiences.

As a Founding Member of Technical Staff, develop and deploy AI systems, lead ML design and workflows, and ensure business impact through scalable AI solutions.

Build AI/ML-powered features across ClickHouse Cloud, designing scalable APIs, integrating inference systems and vector DBs, implementing frontend interfaces, and ensuring production-grade monitoring, versioning, and observability for model deployments.

The Senior Machine Learning Engineer will build and operate ML systems, manage the model lifecycle, and mentor team members while ensuring sustainability data accuracy.

As a Senior Machine Learning Scientist, you will design, build, and optimize deep learning models for biological data analysis, ensuring high-quality outputs and leading complex projects from conception through deployment.

As a Machine Learning Engineer, you'll architect data pipelines, build ML training workflows, integrate event streams, and collaborate with teams to improve model performance and ensure compliance.

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

As a Senior ML Engineer, you will develop ML pipelines, work with language models, and build agentic AI systems while implementing MLOps practices.