Top Remote Machine Learning Jobs in Indianapolis, IN

The QA Data Engineer enhances quality and reliability of data-driven applications by developing automated validation tools, implementing data verification tests, and designing QA architecture for data processing. Responsibilities include performance testing on AI systems, creating data monitoring systems, and exploring new technologies to optimize data QA processes.

As a Senior Machine Learning Engineer at Samsara, you'll develop ML solutions for physical operations, driving new initiatives and optimizing systems. Collaborate with engineering teams to create end-to-end ML applications while influencing industry practices and contributing to company culture.

As a Computer Vision/Machine Learning Engineer at Dandy, you will develop advanced computer vision models, collaborate with product teams, and work on 3D generative AI tasks. Your role involves researching state-of-the-art machine learning methods, managing large datasets, and implementing MLOps best practices to enhance dental technology solutions.

As a Machine Learning Engineer, you will contribute to building and deploying machine learning models for a content recommender system, collaborate with data engineers, and derive insights to improve performance through modeling ideas and feature creation.

The Senior Applied Scientist will leverage advancements in AI/ML, especially in Large Language Models, Computer Vision, and Natural Language Processing, to build complex legal AI agents. Responsibilities include finetuning LLMs, designing scalable frameworks, managing datasets, collaborating with product teams, and leading projects from conception to execution.

You will lead a team to innovate in natural language processing, big data, and artificial intelligence, creating technologies that change digital interaction. This role demands creativity, strong collaboration skills, and the ability to develop prototypes rapidly.

The Machine Learning Architect will design and execute machine learning projects from proof-of-concept to deployment, architecting solutions on cloud platforms such as AWS, GCP, and Azure. The role involves collaborating with business representatives, managing all project phases, and ensuring technical excellence in machine learning delivery while staying current with advancements in the field.