Top Machine Learning Jobs in Miami, FL

The Engineering Manager, Machine Learning will lead a team focusing on 3D deep learning and computer vision, manage the ML roadmap, and implement best practices for MLOps pipelines.

The Sr. Solutions Analyst identifies business problems using advanced analytics, machine learning, and AI techniques, collaborating on innovative solutions with the science team.

As a Research Scientist Intern, you'll work on machine learning problems, prototype features, write production code, and collaborate with mentors.

The Senior Industry Marketing Manager will drive marketing strategy for AI/ML, develop initiatives, create content, and collaborate with sales teams.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

The role involves building and optimizing a machine learning and simulation platform, supporting MLOps, model deployment, and infrastructure modernization, while mentoring engineers.

The Enterprise Account Executive is responsible for selling AppZen's solutions, managing the entire sales cycle, and building relationships with finance executives in Fortune 1000 companies.

Design and apply ontologies and semantic models to transform structured and unstructured data into actionable insights. Develop SPARQL queries, ontology-driven applications, and pipelines using Java, Python, and Bash. Collaborate with clients and lead teams on data exploration, NLP/text-mining, and machine-learning solutions.

As a Knowledge Manager, you will utilize your data science expertise to investigate data sets, develop algorithms, and provide insights to meet client needs across various sectors.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

The role involves designing, optimizing, and deploying machine learning models for edge environments, focusing on computer vision. The engineer will collaborate with teams to integrate models and improve inference efficiency while mentoring peers and upholding company values.

Lead the development of machine learning systems for Cedar's Personalization Engine, focusing on ML modeling, MLOps, and team management to drive healthcare solutions.

As a Product Intern focused on AI & Innovation, you'll research AI tools, prototype workflows, support testing efforts, and collaborate across teams to enhance product management.

The Technical Sales Enablement Manager will design and deliver programs for Solutions Architects and sellers to improve technical competency and sales effectiveness in a fast-paced environment.

As a Senior Data Scientist at Netflix, you'll lead experimentation and statistical modeling in game verticals, influencing data-driven decisions and presenting insights to stakeholders. You'll utilize your extensive experience in data science and statistics to enhance game development processes.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

The Senior Software Engineer will develop ML training pipelines, maintain cloud systems, and optimize the ML lifecycle for dental products.

The Senior ML Ops Engineer will build and maintain infrastructure for AI/ML at scale, manage machine learning models, and support team initiatives while ensuring code quality and engineering standards.

Lead the machine learning and personalization efforts at Babylist, managing a team focused on enhancing product recommendations, search, and revenue through ML initiatives.

The Customer Success Manager at Siena will manage customer portfolios, ensuring measurable outcomes and promoting product usage while fostering collaboration across teams.

Architect and deploy AI-driven documentation and CCMS solutions for regulated life-science environments. Implement NLP/ML tools for content generation, translation, QA, and optimize translation memory and workflows across technical publications.

The Director will lead Macmillan's corporate social media and community growth strategy, enhancing engagement and driving measurable growth across digital platforms through strategic content and analytics.

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

The Director of Machine Learning Engineering is responsible for leading AI strategy, overseeing ML solutions, driving innovation, building teams, and ensuring operational excellence in ML systems.