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Physics Informed Machine Learning Jobs in Frisco, TX

Photon

Machine Learning Engineer - NJ

Addison, TX

$54 - $71.50/hr

We are seeking a Machine Learning Engineer to design and develop robust analytics models using ... Undergraduate or Graduate degree in Computer Science, Mathematics, Physics, or related fields. A ...

AT&T

Senior Data Scientist

Dallas, TX

... analysis, machine learning, and big data technologies to drive informed decision-making and ... or Physics. 3+ years of related experience. Certification is required in some areas. Our Senior ...

AT and T

Senior Data Scientist

Dallas, TX · On-site

... analysis, machine learning, and big data technologies to drive informed decision-making and ... or Physics. 3+ years of related experience. Certification is required in some areas. Our Senior ...

InfoVision, Inc.

Simulation engineer

Irving, TX · On-site

MS or BS in Computer Science,Math, Physics, Information Science, Engineering or other related field ... Knowledge of Artificial Intelligence and machine learning (AI/ML) techniques * Experience in data ...

InfoVision, Inc.

Simulation Engineer

Irving, TX · On-site

MS or BS in Computer Science, Math, Physics, Information Science, Engineering or other related ... Knowledge of Artificial Intelligence and machine learning (AI/ML) techniques * Experience in data ...

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

As of Jul 24, 2026, the average hourly pay for physics informed machine learning in Frisco, TX is $18.78, according to ZipRecruiter salary data. Most workers in this role earn between $11.68 and $23.85 per hour, depending on experience, location, and employer.

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 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 is a Physics Informed Machine Learning job?

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 popular job titles related to Physics Informed Machine Learning jobs in Frisco, TX? For Physics Informed Machine Learning jobs in Frisco, TX, the most frequently searched job titles are:
What job categories do people searching Physics Informed Machine Learning jobs in Frisco, TX look for? The top searched job categories for Physics Informed Machine Learning jobs in Frisco, TX are:
What cities near Frisco, TX are hiring for Physics Informed Machine Learning jobs? Cities near Frisco, TX with the most Physics Informed Machine Learning job openings:
Physics Informed Machine Learning jobs near you
Machine Learning Engineer - NJ

Machine Learning Engineer - NJ

Photon

Addison, TX

$54 - $71.50/hr

Other

Posted 14 days ago

Job description

Summary:

We are seeking a Machine Learning Engineer to design and develop robust analytics models using statistical and machine learning algorithms. In this role, you will work closely with product and engineering teams to solve complex business problems, identify data-driven opportunities, and create personalized experiences for customers. You will be responsible for building end-to-end machine learning solutions, implementing models in production, and working with various data frameworks and tools such as Python, Spark, and Databricks.

Key Responsibilities: Analytics Model Development:

  • Analyze use cases and design appropriate analytics models using statistical and machine learning algorithms tailored to specific business requirements.
  • Develop machine learning algorithms to drive personalized customer experiences and provide actionable business insights.
  • Apply expertise in data mining and machine learning techniques, including  forecasting, prediction, segmentation, recommendation, and fraud detection.

Data Engineering and Preparation:

  • Extend and augment company data with third-party data to enrich analytics capabilities.
  • Enhance data collection procedures to include necessary information for building analytics systems.
  • Prepare raw data for analysis, including cleaning, imputing missing values, and standardizing data formats using Python data frameworks (e.g., Pandas, NumPy).

Machine Learning Model Implementation:

  • Implement machine learning models, considering both performance and scalability using tools like PySpark in Databricks.
  • Design and build infrastructure to facilitate large-scale data analytics and experimentation.
  • Work with tools like Jupyter Notebooks for data exploration and model development.

What We're Looking For:

  • Educational Background: Undergraduate or Graduate degree in Computer Science, Mathematics, Physics, or related fields. A PhD is preferred but not necessary.
  • Experience:
    • At least 5 years of experience in data analytics, with a strong understanding of core statistical algorithms such as classification and regression analysis.
    • High-level knowledge of analytics use cases such as language analysis, assortment optimization, promotional planning, dynamic pricing, markdown optimization, labor scheduling, and optimization.
  • Technical Skills:
    • Strong experience with Python-based machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
    • Proficiency in using analytics platforms like Databricks for large-scale data processing.
    • At least 4 years of continuous experience with Spark, particularly PySpark implementation.
    • Hands-on experience with data processing and analysis tools such as Pandas, NumPy, and Jupyter Notebooks.

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