Top Machine Learning Jobs in Miami, FL

Lead the development of agentic AI systems for real estate, focusing on long-horizon, supervised experiences. Architect collaborative systems and define success metrics while mentoring a small team.

Lead the development of intelligent decision engines modeling customer intent in real-time using advanced data science techniques such as causal inference and machine learning. Collaborate with cross-functional teams to optimize systems for search, fulfillment, and customer experience.

As a Machine Learning Engineer, you'll design AI/ML solutions, optimize pipelines, integrate models, and enhance AI capabilities while collaborating with teams.

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.

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.

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.

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

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

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

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

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

As the Data Science Lead for Monetization, you'll shape monetization strategy, lead the data science team, and drive decision-making through measurement and experimentation.

Lead technical pre-sales engagements, design tailored solutions, demonstrate platform capabilities, assess customer needs, and expand relationships within life sciences and health technology.

The Vice President leads late-stage respiratory programs, manages clinical teams, ensures compliance, and oversees strategic execution in respiratory medicine trials.

The SVP of AI Innovation - Web Scraping will lead the development of AI-driven web scraping strategies, focusing on data acquisition, technology enablement, compliance, team building, and cross-functional collaboration for new data services.

The Product Manager will identify process improvements and innovations, utilize automation and AI, and manage the product lifecycle to enhance productivity and deliver business value.

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.

The Director of AI & Automation will strategize and implement AI, automation, and machine learning initiatives, improving operational efficiency and user experiences.

Seeking a strategic eDiscovery lawyer with 10+ years in complex litigation, expertise in eDiscovery processes, and leadership skills to drive innovation.

The Associate Director leads the Global Records and Information Management team, optimizing governance practices, managing projects, and developing relationships across various stakeholders, while ensuring regulatory compliance and strategic implementation.

The Technical Account Manager (TAM) ensures technical success for Genesys customers by building relationships, managing adoption, and providing technical expertise.

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 Data Scientist Consultant II leads data-driven decision-making through the development of predictive modeling algorithms and effective use of machine learning techniques to solve business problems and improve outcomes.

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 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.