Top Senior Machine Learning Jobs in Miami, FL

As a Senior Machine Learning Engineer, you will develop and deploy AI-driven products to enhance clinical trials, collaborating with teams to improve patient care through scalable machine learning solutions.

As a Senior Machine Learning Engineer, you will drive AI initiatives, collaborate across teams, and develop scalable ML infrastructure to improve healthcare.

As a Senior AI Engineer, you will develop and optimize Generative AI applications, manage AI pipelines, collaborate with clients, and ensure production delivery with MLOps best practices.

The AI Strategist leads AI initiative ideation and planning, collaborates across departments to define use cases, and ensures alignment with strategic and regulatory goals.

The role involves improving machine learning ranking models, implementing algorithms, and taking full ownership of machine learning systems within Quora's product.

The Staff ML Research Scientist will lead research in deep learning for drug discovery, develop innovative models, and integrate them into commercial software. Responsibilities include mentoring junior researchers and contributing to scientific publications.

In this role, you will design and develop AI and machine learning models, maintain data pipelines, evaluate model performance, and collaborate with cross-functional teams to integrate AI capabilities into web-based applications.

As a Senior ML Engineer, you will lead the design and operation of GenAI solutions, focusing on LLM development and deployment, mentoring colleagues, and collaborating with cross-functional teams to enhance AI capabilities for the insurance sector.

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

As a Staff Machine Learning Engineer, you will develop, productionize, and deploy ML models for clinical use, ensuring real-world effectiveness through hands-on coding and infrastructure building.

Serve as an AI/ML-focused solution engineer for Healthcare & Life Sciences: provide technical guidance, design cloud data and lakehouse architectures on Snowflake, lead demos and proofs-of-concept, support sales cycles, collaborate with product and engineering, and communicate AI/ML value to technical and executive stakeholders.

The Staff Machine Learning Engineer will develop and maintain MLOps tools, optimize model performance, and collaborate on ML system architecture with a focus on enhancing developer experience.

As a Senior MLOps Engineer, you will manage production ML systems, define lifecycle strategies, optimize ML pipelines, and collaborate with cross-functional teams to enhance ML operations.

The role involves building bioinformatics and ML pipelines, analyzing multi-omics data, mentoring, and collaborating across teams to develop actionable insights and scientific breakthroughs.

Lead design, development, and productionization of advanced ML models and data pipelines. Drive architecture, experimentation, validation, and best practices while mentoring ML engineers and delivering scalable, business-driving AI solutions.

The Machine Learning Engineer will design and build systems that improve the AI shopping agent by using real user feedback, focusing on feedback loops and metrics to enhance user interactions and agent performance.

As an ML Platform Engineer, you will enhance the core ML platform's performance and scalability, enabling faster innovation and impactful machine learning solutions.

Lead and grow a global data engineering and ML organization, design cloud-native data platforms and pipelines, deliver ML-powered products, establish engineering and MLOps best practices, and support sales through solutioning and client-facing technical leadership.

Manage and mentor a team of machine learning and data engineers, overseeing ML model development, data pipelines, and collaborating with product teams on technical requirements.

Design and operate production ML systems for large-scale streaming data, ensuring reliability and performance while collaborating with researchers to integrate models into distributed systems.

The AI Director will oversee ML bot development and implementation, identify AI opportunities, educate teams, and prototype AI solutions.