Top Machine Learning Jobs in Memphis, TN

Lead the development of AI-driven security workflows, integrate machine learning models, establish data pipelines, and mentor engineers.

Lead product managers overseeing distribution and onboarding experiences, drive product execution, manage a team, and advocate for user needs.

The AI Data Specialist will perform tasks like data collection and evaluation, annotation, pairwise comparisons, and object tagging to enhance AI-generated content.

The role involves designing and implementing scalable ML-based solutions, analyzing data patterns, and producing reports while staying updated on AI advancements.

This role involves developing and integrating AI/ML models within GCP using Python, optimizing LLM performance, and applying MLOps practices. Strong collaboration with architects is required for implementation and analysis of workflows.

The Senior Product Manager will develop AI tools, collaborating with research, engineering, and design to meet user needs and drive business value.

The role leads predictive modeling and machine learning initiatives, mentors team members, and drives innovations in data science for credit risk and operations.

The Staff ML Ops Engineer builds and maintains infrastructure for ML applications, ensuring they are robust and production-ready, while collaborating with data scientists and ML engineers.

The role involves developing scalable ML solutions, leading cross-functional discussions, analyzing knowledge data, and producing technical documentation to improve search relevance using AI and machine learning technologies.

The Technical Product Manager will enhance platform capabilities, partner with Engineering, evaluate APIs and data systems, and define product requirements to drive technical initiatives.

The Principal Software Engineer will lead multi-year initiatives at SmithRx, focusing on technical strategy, system design, and cross-functional collaboration while mentoring engineers and driving engineering excellence.

As a Software Engineering Intern, you'll develop features for user-facing products, work on API platforms, and design data pipelines while gaining hands-on experience in AI technologies.

Join Clarity AI's Talent Community by submitting an open application for various roles in product, technology, finance, marketing, or operations to drive positive impact.

Lead the design and optimization of programmatic bidding systems, collaborating with engineers and applying analytical methodologies to enhance performance.

The role involves improving recommendation systems using machine learning, developing end-to-end ML systems, and collaborating with engineers.

The Data Scientist will develop machine learning models to optimize software build processes, analyzing large datasets and collaborating with teams for improvements.

The Principal Machine Learning Engineer will improve diffusion models, conduct research, implement techniques, and collaborate on production-ready systems in AI for fashion.

The Principal Machine Learning Engineer will lead ML lifecycle projects, developing AI strategies, and implementing advanced machine learning solutions for government clients, while ensuring data integrity and operational efficiency.

The Senior Software Engineer will design and build infrastructure for ML model training and deployment, focusing on AWS technologies, reliability, and collaboration with ML teams.

The Machine Learning Solutions Architect designs and implements data solutions, overseeing model deployment and ensuring robust performance and integration within customer environments.

The Senior Machine Learning Engineer at SmarterDx will deploy, maintain, and optimize machine learning models, collaborating across disciplines to integrate these solutions and improve clinical AI outcomes.

Design and architect AI/ML solutions, build document parsers and classifiers, maintain AI systems, and collaborate with cross-functional teams.

As an Applied Scientist, you will design and implement machine learning models, develop personalized systems, and enhance decision-making through AI technology to improve user experience and business operations.

The Engineering Manager will lead the development of the Ad Platform infrastructure, ensuring high quality, efficiency, and accountability across systems while embedding AI and managing big data operations.

As a Machine Learning Customer Success Engineer, you will facilitate ML workflows, manage user relationships, and contribute to FiftyOne's development.