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

Crowe LLP

Machine Learning Intern

Fort Lauderdale, FL · On-site

$27 - $42/hr

Role Summary The data science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will ...

Crowe LLP

Machine Learning Intern

Miami, FL · On-site

$27 - $42/hr

Role Summary The data science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will ...

Deloitte

Senior AI Engineer - SFL Scientific

Miami, FL · On-site

$99K - $137K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

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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 Researcher - PhD Intern (US)

Citadel Securities

Miami, FL

$112.50 - $145/hr

Full-time

Re-posted 6 days ago

Job description

Job Description

At Citadel Securities, a leading global market maker, our team of quantitative researchers models the markets and brings trading strategies to life every day. Specifically, the goal of this team is to leverage and tailor the state-of-the-art machine learning and AI algorithms to modernize the quantitative trading industry. We're looking for extraordinary and highly motivated researchers who are excited about solving challenging problems and iterating in a fast-paced environment.

As an intern, you'll get to challenge the impossible in research through an 11 week program that will allow you to collaborate and connect with senior team members. In addition, you'll get the opportunity to network and socialize with peers throughout the internship.

Our signature internship program takes place June through August. Occasionally, we can be flexible to other times of the year. You will be able to indicate your timing preference in the application.

Your Objectives

  • Use statistics, machine learning or AI (e.g. deep learning, NLP) to extract patterns from various kinds of datasets through innovative and rigorous research
  • Implement algorithms in high-quality code
  • Work with large data sets, including unconventional and unstructured data sources
  • Back-test models and document research findings

Your Skills & Talents

  • PhD degree in mathematics, statistics, physics, computer science, or another highly quantitative field
  • Advanced training and strong research track record in statistics, machine learning, AI, or another highly quantitative field
  • Hands on programming experience in scripting (e.g. Python) and/or compiled languages (e.g. C++)
  • A background demonstrating strong problem-solving skills
  • An ability to communicate advanced concepts in a concise and logical way
  • Proficiency in creating and using algorithms to meticulously investigate and work through large data or error-checking problems

Opportunities may be available from time to time in any location in which the business is based for suitable candidates. If you are interested in a career with Citadel Securities, please share your details and we will contact you if there is a vacancy available.

In accordance with applicable law, the base salary range for this role is $4,500 to $5,800 per week.

About Citadel Securities

Citadel Securities is a technology-driven, next-generation global market maker. We provide institutional and retail investors with world-class liquidity, competitive pricing and seamless front-to-back execution in a broad array of financial products. Our teams of engineers, traders and researchers harness leading-edge quantitative research and the accelerating power of compute, machine learning and AI to power our analytics and tackle the market's and our clients' most critical challenges. Together, we are forging the future of capital markets. For more information, visit citadelsecurities.com .

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