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Physics Informed Machine Learning Jobs in Pembroke Pines, FL

Qfanalytics

Machine Learning Engineer

Miami, FL · On-site

$80 - $120/hr

Required Qualifications Master's Degree in Mathematics, Engineering, Physics or related field ... in Machine Learning; Experience with deep learning frameworks like TensorFlow or PyTorch;

Deloitte

Senior AI Engineer - SFL Scientific

Miami, FL · On-site

$99K - $137K/yr

... Physics, etc.) or equivalent experience • 4+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment • 4+ ...

Pae

AI Modeling Specialist (Senior)

Doral, FL

Design, develop, and deploy machine learning, artificial intelligence, and advanced statistical ... informed outputs). Required Qualifications: * Must have an active Top-Secret security clearance and ...

Pwc

AI Engineer

Boca Raton, FL · On-site

$50K - $112K/yr

... informed decision-making and driving business growth. Within our Internal Firm Services practice ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

Pwc

AI Engineer

Miami, FL · On-site

$50K - $112K/yr

... informed decision-making and driving business growth. Within our Internal Firm Services practice ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

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Physics Informed Machine Learning information

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How much do physics informed machine learning jobs pay per hour?

As of Aug 18, 2026, the average hourly pay for physics informed machine learning in Pembroke Pines, FL is $18.62, according to ZipRecruiter salary data. Most workers in this role earn between $11.59 and $23.65 per hour, depending on experience, location, and employer.

What is a physics informed machine learning?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What are the typical challenges faced by professionals working in physics informed machine learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.

What are the key skills and qualifications needed to thrive in the physics informed machine learning position, and why are they important?

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are popular job titles related to Physics Informed Machine Learning jobs in Pembroke Pines, FL?

For Physics Informed Machine Learning jobs in Pembroke Pines, FL, the most frequently searched job titles are:

What cities near Pembroke Pines, FL are hiring for Physics Informed Machine Learning jobs?

Cities near Pembroke Pines, FL with the most Physics Informed Machine Learning job openings:

Physics Informed Machine Learning jobs near you

Machine Learning Engineer

Qfanalytics

Miami, FL • On-site

$80 - $120/hr

Other

Posted 13 days ago

Job description

QF Analytics LLC is a fintech company that develops and supports one of the world’s fastest-growing online trading platforms with a monthly trading volume in excess of $11 billion dollars. We are expanding our team aggressively and looking ideally for individuals with trading domain knowledge, who can help develop and support a robust financial trading infrastructure.

The Machine Learning Researcher should be interested in Financial Markets, and will be directly involved in advancing the company’s Data Analysis and Machine Learning capabilities. They’ll be working on cutting edge Quantitative Data Analysis and Machine Learning challenges. Our environment is fast paced and constantly changing; the right candidate must be able to demonstrate strong communication skills, creative solutions, and results-driven behavior in time-sensitive situations.

This opportunity presents an exciting chance for individuals seeking a dynamic work environment. The successful candidate will have the option to work in a hybrid capacity, commuting to offices in Miami, Chicago, Atlanta, Toronto (Canada) or Nassau (Bahamas), fostering a collaborative and engaging atmosphere. Join our team and experience the synergy that comes from working together in person, while also enjoying the flexibility and convenience of working from home a couple days a week.

Responsibilities

Apply strong data modelling and statistical skills to develop and implement data-driven solutions.

Curate and prepare data for supervised and unsupervised machine learning projects, ensuring data quality and compatibility.

Manipulate and analyze large datasets, including numerical and categorical data, using appropriate techniques and tools.

Utilize knowledge of classical machine learning and deep learning algorithms to address specific problem domains.

Apply ML/AI tools like TensorFlow/PyTorch to build and train models for various applications.

Interface with databases to gather relevant information for analysis and modeling.

Fuse and correlate different data feeds to gain insights and enhance predictive capabilities.

Stay updated with the latest advancements in the field of machine learning and artificial intelligence, including tools, conferences, and industry blogs.

Possess a solid understanding of capital markets concepts and quantitative financial methods to effectively apply machine learning techniques in finance-related projects.

Required Qualifications

Master’s Degree in Mathematics, Engineering, Physics or related field;

Proficiency in Python;

Strong understanding of SQL for data manipulation and extraction;

Solid knowledge of probability and statistics to effectively analyze and interpret data;

Knowledge of applied mathematics, including convex optimization, quadratic programming, and partial differential equations;

Proficiency in analyzing and interpreting data, along with the ability to question it and draw meaningful conclusions;

Hands‑on approach and flexibility to apply various methods and techniques to generate actionable ideas;

Proactive, self‑motivated, and team‑oriented mindset, demonstrating strong analytical thinking;

Strong conceptualization, innovation, and problem‑solving skills;

Ability to communicate effectively through verbal and written presentations;

Preferred Qualifications

PhD in Mathematics, Engineering, Physics or related field;

4-8 years experience working in Machine Learning;

Experience with deep learning frameworks like TensorFlow or PyTorch;

Familiarity with C# and .NET framework;

Familiarity with Azure Environments; specifically Azure Data Functions;

Familiarity with Docker initialization and environment management.

What We Have To Offer

Flexible work arrangements when in office (including working from home periodically);

Competitive salaries, often better than industry, for comparable roles;

Daily premium lunch catering, and keeping the office stacked with fruits and snacks;

Arcade, foosball, snooker, pingpong, and fully equipped game room with latest generation gaming consoles on site;

Comprehensive health benefits plan that kicks in after 90 days of successful employment, including access to exclusive employee discounts;

Bonus and incentive programs.

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