Top Machine Learning Jobs in Atlanta, GA

The Machine Learning Engineer Intern at Hugging Face will expand tools for users to understand and write Gradio code. They will engage with Gradio's vast library and assist in building sophisticated model pipelines, ensuring context for developers using LLMs.

The role involves expanding Hugging Face's ecosystem for web developers by creating and maintaining machine learning libraries in JavaScript and TypeScript, optimizing models for browser inference, and building demo applications. It combines software engineering with machine learning and fosters open-source collaboration.

The Machine Learning Engineer will focus on integrating Hugging Face models with AI hardware, ensure model performance, create user-friendly Python APIs, and deploy models efficiently.

The AI/ML Solution Architect will design and implement AI and machine learning features for ValGenesis products. Responsibilities include building scalable models, image processing solutions, and AI architecture, while ensuring compliance with industry regulations. The role involves collaboration with cross-functional teams and mentoring AI/ML engineers.

The Machine Learning Engineer at Ritual will automate Data ETL pipelines, deploy machine learning models, and develop customer-facing products. Responsibilities include scaling up model inference, connecting ML models to human interfaces, and designing large-scale data and ML pipelines while collaborating with cross-functional teams to innovate AI products.

As a Software (ML Product) Engineer, you will enhance the user experience of ML tools by optimizing workflows and processes. You will collaborate with technical product managers, contribute to defining efficient ML practices, and improve DVC, an open-source tool for machine learning. A strong background in deep learning and system design is necessary to transform current workflows and engage with the ML community.

The Group Product Manager will lead the development of innovative technologies for tvScientific's connected TV advertising platform. This role involves product strategy, market research, collaboration with cross-functional teams, and establishing key performance indicators to optimize advertising performance.

The Machine Learning Infrastructure Engineer will design and maintain scalable infrastructure for machine learning models, working alongside data scientists and engineers. Responsibilities include implementing infrastructure-as-code, deploying models efficiently, optimizing performance, and ensuring data security and integrity.

The Machine Learning Engineer/Applied Researcher will train and fine-tune Large Language Models, implement supervised fine-tuning techniques, collaborate with teams on experiments, optimize training pipelines, and document findings. The role requires expertise in modern ML practices and effective communication skills to convey technical concepts to various stakeholders.

As a PhD Machine Learning Research Intern at Cresta, you will collaborate with leading researchers and engineers, contributing to AI advancements by developing algorithms for product deployment. You'll analyze the efficiency and scalability of algorithms, communicate findings to stakeholders, and publish research in top AI venues.

The Senior Machine Learning Engineer role at Step involves designing, developing, and deploying machine learning models for risk and fraud detection, leading technical efforts, data manipulation using SQL, and collaborating with cross-functional teams.

The Sr. Manager, Machine Learning Engineering will lead a team of ML researchers and engineers, focusing on representation learning. Responsibilities include managing team charters, advocating for efficient ML techniques, collaborating with data scientists, and guiding strategic direction for representation learning.

The Machine Learning Customer Engineer will partner with users to design, build, and troubleshoot AI applications, resolving critical technical issues and assisting in product adoption. This role involves collaboration with various teams, improving customer support, and voicing customer needs for product development.

The Machine Learning Solutions Engineer acts as a technical advisor throughout the sales cycle, collaborating with customers to design tailored technology evaluation processes and educate them on the Snorkel Flow platform. Responsibilities include building presentations, guiding customers on AI strategies, and working closely with sales to meet targets while ensuring successful hand-offs to post-sales teams.

As a Staff Machine Learning Engineer, you will lead projects in Inclusive AI, ensuring fairness in ML applications, mentor junior engineers, and collaborate with other teams on technical strategies to drive significant improvements in user experience. You'll work on state-of-the-art ML models and ensure they operate fairly and inclusively at scale.

The Manager of Fraud Machine Learning will oversee fraud detection capabilities at Extend, managing a team of data scientists to develop machine learning models that prevent and identify fraud across various products. This role involves leading technical implementation, collaborating with product and engineering teams, mentoring junior staff, and enhancing the culture of learning within the organization.

As the Machine Learning Manager for Ads Targeting Modeling at Reddit, you will define and drive the engineering strategy for targeting products. Your responsibilities include developing machine learning-powered targeting features, overseeing execution and quality of projects, scaling the team, and promoting career development for team members.