Top Machine Learning Jobs in Atlanta, GA

Design, build, and scale production ML systems (including LLMs) to automate customer support and compliance workflows. Lead technical roadmaps, write high-quality Python code, mentor engineers, ensure secure, scalable architectures, and resolve complex reliability issues.

Design, build, and deploy scalable ML models and data pipelines for prediction, anomaly detection, personalization, and automation. Own operationalization, monitoring, model evaluation, and integration with platform services at cloud scale.

The Sr. Machine Learning Engineer will build tooling and services for ML and generative AI solutions, focusing on deployment, evaluation metrics, and cross-functional collaboration.

As a Lead Data Scientist, you will design end-to-end analytical solutions, develop ML infrastructure, and collaborate with clients to deliver insights and manage solutions.

Lead the Machine Learning Engineering team at AKASA, focusing on improving ML capabilities, model deployment, and infrastructure development, while managing and mentoring engineers.

As a Machine Learning Engineer, you will develop and operationalize models for content understanding and discovery, collaborating with cross-functional teams and stakeholders to solve impactful problems using machine learning.

Lead the Client Solutions team, ensuring the execution of complex transactions while driving innovation and client advocacy. Oversee operations, build client relationships, and implement strategic frameworks for growth.

Participants are needed for an AI technology research study, offering compensation up to $600 for ~1.5-2 hours of participation over one week, requiring skills in tech-related roles.

As a Senior Machine Learning Engineer, you'll develop models for risk identification, collaborate cross-functionally, and deploy ML solutions, ensuring performance monitoring and continuous improvement.

Lead the vision, strategy, and execution of the machine learning platform at Flex, focusing on compliance, customer success, and internal operations. Build and mentor a team of ML engineers and data scientists to deliver scalable ML systems.

The Business Analyst 2 analyzes AI-powered data solutions, optimizes customer experience automation, and collaborates with teams to drive business insights and value.

The Research Scientist will conduct studies on natural language processing and machine learning, transition models to production, conduct experiments, publish research, and create new models to enhance products.

The Engagement Principal is responsible for the deployment of Aera solutions, managing client relationships, project delivery, and contributing to sales cycles, ensuring successful implementation and value delivery.

The Marketing Manager will lead strategic campaigns, manage content, collaborate with teams, analyze performance, and stay ahead of industry trends to drive brand awareness and customer engagement.

Lead a team to develop groundbreaking technology combining NLP, big data, and AI to enhance digital communication and interaction.

The GTM role focuses on increasing revenue through new sales and partnerships, understanding client needs, and communicating product value.

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.

Build and own full-stack UX and backend systems for the ML lifecycle: design architecture, integrations, observability, CI/CD, and production frontend/backends. Lead technical initiatives, mentor engineers, and collaborate across teams to scale ML platform capabilities.

The role involves defining AI strategy for the AECO industry, prioritizing AI use cases, and guiding AI initiatives to align with Autodesk's portfolio.

The Senior ML Engineer will build, deploy, and support machine learning models on AWS, collaborating with data scientists and maintaining deployment pipelines.

Develop and deploy AI-driven text-to-speech solutions, ensuring production reliability and optimizing performance, collaborating with engineers and researchers.

As a Software Engineer at Speechify, you will work with machine learning teams to enhance AI Voice functionalities, manage deployments, and improve model efficiency.

The Director of Product Engineering leads the product engineering organization, overseeing technical direction, talent management, engineering excellence, and collaboration across teams to deliver secure, reliable digital products.

As a Principal Data Scientist, you'll design and deploy cutting-edge machine learning models to drive financial success for customers and guide technical teams.

As a Senior Solution Consultant, you'll advise clients on identity verification solutions, lead technical workshops, and collaborate with sales and engineering teams to ensure client satisfaction and product alignment.