Top Remote Machine Learning Jobs in Miami, FL

Lead architectural vision and development of scalable infrastructure for self-driving technology, mentoring engineers and overseeing complex projects.

Develop and optimize deep learning models for trajectory generation in autonomous vehicles, focusing on planning, control, and real-time inference.

Design and build ML infrastructure components for autonomous vehicles, ensuring scalability and robustness for high-volume data processing and model training.

The Senior Solution Innovation Architect will design and implement AI/ML solutions on the Snowflake platform, collaborate with customers, and provide technical expertise in ML and AI applications.

As a Machine Learning Engineer at Shipwell, you'll build and scale AI-powered logistics solutions, maintaining data pipelines and ML infrastructure across the organization.

The role involves developing advanced multimodal customer experiences using AI, mentoring others, and refining AI processes for Zillow's platforms.

The Senior Power System Studies Engineer designs and applies AI/ML techniques for power system optimization, conducts simulations, and mentors junior engineers.

The position involves driving AI/ML product development for personalized experiences, partnering across teams, and launching impactful products.

As an ML Solutions Architect, design, implement, and lead machine learning solutions for Conversation AI, collaborating with cross-functional teams to address complex business challenges.

The Senior Machine Learning Consultant designs and develops machine learning solutions while mentoring team members and collaborating with clients. Responsibilities include conducting R&D on AI/ML models, optimizing model performance, and ensuring adherence to ethical AI practices.

The role involves building ML infrastructure, creating data pipelines, ensuring data quality, and collaborating with data scientists to optimize models.

The role involves designing and implementing distributed systems for batch inference workloads, creating developer-friendly APIs, and fostering engineering excellence.

Drive the development of AI solutions for payments, ensuring low latency and high reliability, while mentoring teams and collaborating cross-functionally.

As a Staff Machine Learning Engineer, optimize card pricing models, lead ML lifecycle, collaborate with experts, and enhance predictive features.

As a Senior Staff Machine Learning Engineer, you'll lead projects on ML models for search and recommendations, impacting over 150M users. Responsibilities include improving ML systems, collaborating with cross-functional teams, and developing infrastructure for model deployment.

The role involves designing, building, and managing data pipelines and machine learning solutions for veterinary care, utilizing cloud services and various programming languages while collaborating within an Agile team.

The Staff Machine Learning Engineer at Niche will lead ML initiatives, build and deploy models, measure results, mentor staff, and drive business growth through data-driven solutions.

The Senior Machine Learning Engineer will personalize user experiences, build systems for model training, collaborate with cross-functional teams, and contribute to product strategy.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

The Senior Software Engineer will own large-scale data mining workflows, improve ML products through high-quality datasets, and analyze model performance across driving scenarios.

Lead AI and machine learning projects, create workflows and models, analyze data from diverse sources, and present insights to non-technical audiences.

The AI & Machine Learning Director will lead machine learning projects, design data workflows, and utilize advanced data analysis and visualization to drive business insights.

As an AI/ML Data Engineer, you will design and build data and ML infrastructure to create personalized student experiences, working on ETL processes, feature stores, and collaborating with product and data science teams.

Lead development of a large-scale machine learning platform, optimizing model training, data processing, and collaborating on MLOps, while ensuring scalability and performance.

Lead development of data pipelines and workflows for ML models, design scalable data processing environments, and ensure high data quality.