Top Machine Learning Jobs in Atlanta, GA

As Director of AI/ML, lead the ML organization, set technical vision, mentor a high-performing team, and contribute to model development and production deployment.

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.

The Senior Product Manager will own the roadmap and execution of a real-time data platform, leading product strategy, discovery, and commercialization while collaborating with cross-functional teams to enhance data-driven insights and product performance.

As a Staff Machine Learning Engineer, you will optimize Quora's ad products by applying machine learning algorithms, taking ownership of systems, and collaborating across teams.

Lead the Applied ML team's experimentation efforts, mentoring scientists and engineers to improve AI-driven methodologies and collaboration across various product areas.

You will lead technical strategy and engineering for ML-powered messaging features at Airbnb, integrating solutions and collaborating with teams to enhance user communication. Responsibilities include system design, mentoring, and establishing engineering standards.

The AI Forward Deployed Engineer designs and implements AI solutions, collaborating with stakeholders, enhancing reliability, and producing reusable resources. Responsibilities include diagnosing AI solution issues and engaging with finance and data teams.

Partner with CV researchers to productionize models, optimize training and real-time inference performance, design reusable abstractions, and collaborate with MLOps/backend teams to evolve the CV inference platform for scale and reliability.

The Staff Machine Learning Engineer will lead AI initiatives, architect LLM systems, design evaluation frameworks, and mentor engineers.

The Staff Advanced Analyst will drive data analytics to improve CS Safety experiences, influence product decisions, and build measurement tools using data-driven insights.

The Director of Data Sciences leads a team in strategic initiatives, drives machine learning and AI solutions, and manages resources to enhance data-driven decision making across the business unit.

Lead the Marketplace engineering team to enhance the renter experience by developing scalable systems, managing teams, and collaborating with cross-functional stakeholders to drive product strategy.

As Engineering Manager for the Marketplace team, lead full-stack engineers, drive strategic vision, manage team processes, and enhance user experience using AI and ML innovations.

The Customer Success Manager will manage post-sales relationships, drive customer engagement and ROI, and advocate for client needs within the Buzz Solutions platform.

The role involves leading a team to manage data strategies and analytics for Netflix Games, requiring expertise in data science, business analytics, and team management.

As a Solutions Engineer, you will drive sales growth, support partnerships, and deliver AI-driven solutions while collaborating with various teams.

The Product Manager will lead the development of data-driven product capabilities at Axuall, ensuring features are delivered on time and meet customer needs through collaboration with various teams.

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.