Top Machine Learning Jobs in Miami, FL

The role involves designing, building, and optimizing large-scale ML systems for personalized recommendations, focusing on data ingestion, model training, and collaboration with cross-functional teams.

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

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 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.

Lead research and development of advanced fraud detection ML models, experiment design, productionizing prototypes, and mentoring engineers.

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 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.

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

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

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

The Machine Learning Annotation Content Developer creates instructional materials for data annotation workflows, developing content for text, image, video, and audio. Responsibilities include producing materials, hands-on exercises, and iterative content revisions while collaborating with the program team to align on learning outcomes.

The role involves designing and deploying AI applications using LLMs, optimizing deep learning models, and collaborating with teams to integrate AI solutions into workflows.

Lead the development of AI systems and models, optimize workflows, manage data engineering efforts, and mentor junior engineers in AI and ML best practices.

The role involves automating and maintaining AWS infrastructure, collaborating with engineering teams for deployment, optimizing ML infrastructure, and ensuring compliance and security standards in a cloud-native environment.