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Scientific Machine Learning Jobs in Miami, FL (NOW HIRING)

Prescient Edge

Senior Data Scientist

Doral, FL · On-site

Job Title Senior Data Scientist Location Doral, FL 33122 US (Primary) Category Intelligence Job ... Possess the knowledge and capability to develop advanced machine learning models and optimize ...

Lynker

Marine Sensor Data Scientist - AI/ML

Miami, FL · On-site

$110 - $160/hr

Support or lead the development of machine-learning detectors and classifiers for sensor data. * Develop, train, test and validate analytical models. * Generate science products that can be used by ...

Deloitte

Senior AI Engineer - SFL Scientific

Miami, FL · On-site

$99K - $137K/yr

... machine learning applications. Responsibilities : • Work with clients to design, develop, and ... Required : • Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.) or ...

YO AI Labs

AI Data Scientist Expert - Remote

Miami, FL · Remote

$100 - $200/hr

Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning, Applied AI, Statistics, Quantitative Analytics, or Data Analytics. * Experience producing or ...

Agile Defense

Data Scientist

Doral, FL · On-site

This role is part of a multidisciplinary team integrating advanced analytics, machine learning, and ... science, machine learning engineering, or data pipeline development. * Proficient in Python, SQL ...

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All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in Miami, FL

Scientific Machine Learning information

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How much do scientific machine learning jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for scientific machine learning in Miami, FL is $30.11, according to ZipRecruiter salary data. Most workers in this role earn between $18.41 and $38.41 per hour, depending on experience, location, and employer.

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are the key skills and qualifications needed to thrive as a scientific machine learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Miami, FL?

For Scientific Machine Learning jobs in Miami, FL, the most frequently searched job titles are:

What job categories do people searching Scientific Machine Learning jobs in Miami, FL look for?

The top searched job categories for Scientific Machine Learning jobs in Miami, FL are:

What cities near Miami, FL are hiring for Scientific Machine Learning jobs?

Cities near Miami, FL with the most Scientific Machine Learning job openings:

Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Miami, FL as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $62,621 per year, or $30.1 per hour.

Machine Learning Engineer in Sunrise, FL (Onsite, Fulltime Only - No C2C)

Northern Base

Sunrise, FL • On-site

Full-time

Re-posted 20 days ago

Job description

Role -  Machine Learning Engineer
Experience Required -8+ Years
Sunrise, FL
Fulltime
 
 
 
Must Have Technical/Functional Skills:
We are seeking a Machine Learning Engineer to design, build, and deploy Generative AI solutions powered by Large Language Models (LLMs). In this role, you will work on end-to-end GenAI use cases, from model selection to production-ready systems. Key Responsibilities Develop and productionize GenAI applications using LLMs (open-source and closed-source). Design agentic workflows using LangChain and LangGraph.
• Implement short-term and long-term memory strategies for LLM-based systems.
• Optimize prompts, retrieval pipelines, and orchestration logic.
• Collaborate with product and platform teams to deliver scalable AI solutions.
Required Qualifications 
• Strong experience with LLMs (e.g., OpenAI, Anthropic, Llama, Mistral)
• Hands-on experience with LangChain and/or LangGraph.
• Solid understanding of LLM memory architecture and state management.
• Proficiency in Python and ML engineering best practices.
Nice to Have
• Experience with GCP services (e.g., Vertex AI, BigQuery, GCS).
• Experience deploying ML/GenAI systems in production environments.
• data scientist
• Can do ML model
 
Roles & Responsibilities
• Design, develop, and deploy GenAI applications using LLMs.
• Build and implement agentic workflows using LangChain/LangGraph.
• Develop ML models and production-ready AI solutions.
• Implement and manage LLM memory and state management strategies.
• Optimize prompts, retrieval pipelines, and orchestration workflows.
• Collaborate with product and platform teams to deliver scalable AI solutions.
• Deploy, monitor, and maintain AI/ML systems in production environments.
• Evaluate and integrate open-source and proprietary LLMs.