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Physics Informed Machine Learning Jobs in Fort Worth, TX

Neara

Forward Deployed Engineer - USA (Dallas)

Dallas, TX · On-site

$130K - $200K/yr

We use advanced machine learning to create engineering-grade, physics enabled digital twins of electricity grids across four continents, this helps asset owners understand their biggest challenges ...

Pwc

Tax Innovation - AI Engineer - Senior Manager

Dallas, TX · On-site

$124K - $335K/yr

... informed decision-making What You Must Have - At least a Bachelor's degree - At least 6years of ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

New

AIIR Holdings Inc.

HVAC System Engineer

Addison, TX · On-site

... machine learning technology. Our flagship product, the AIIR Intelligent HVAC system, delivers ... Thorough knowledge of the engineering fundamentals and the underlying physics of HVAC systems.

AIIR

HVAC System Engineer

Addison, TX · On-site

... machine learning technology. Our flagship product, the AIIR Intelligent HVAC system, delivers ... Thorough knowledge of the engineering fundamentals and the underlying physics of HVAC systems.

Prattwhitney

Algorithm Principal Systems Engineer

Plano, TX · On-site

$107.50 - $204.50/hr

Bachelor's degree in a STEM discipline such as engineering, physics, or mathematics. * Eight (8) ... machine learning. * UNIX/Linux proficiency and proven programming skills in C/C++ and MATLAB or ...

Pwc

CTIO - AI Engineer- Senior Manager

Dallas, TX · On-site

$91K - $321K/yr

... informed decision-making and driving business growth. Within our Internal Firm Services practice ... the implementation of machine learning algorithms and predictive modeling techniques ...

Pwc

CTIO - AI Engineer- Senior Manager

Fort Worth, TX · On-site

$91K - $321K/yr

... informed decision-making and driving business growth. Within our Internal Firm Services practice ... the implementation of machine learning algorithms and predictive modeling techniques ...

Pwc

CTIO AI Engineering Manager

Dallas, TX · On-site

$73K - $244K/yr

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at ...

Pwc

CTIO AI Engineering Manager

Fort Worth, TX · On-site

$73K - $244K/yr

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at ...

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

As of Aug 21, 2026, the average hourly pay for physics informed machine learning in Fort Worth, TX is $19.23, according to ZipRecruiter salary data. Most workers in this role earn between $11.97 and $24.42 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.

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Physics Informed Machine Learning jobs near you

Forward Deployed AI Engineer (Palantir)

Everest Technologies, Inc.

Dallas, TX • On-site

Full-time

Posted 15 days ago

Job description

Here is the updated Job Description with Palantir Platform & Ecosystem experience (AIP, Foundry, Ontology) seamlessly integrated across the Overview, Responsibilities, and Qualifications.
Job Description: Forward Deployed AI Engineer
Role Overview
As a Forward Deployed AI Engineer, you will sit at the intersection of AI engineering, product strategy, and enterprise client delivery. Working closely with enterprise partners, you will own the end-to-end strategy, architecture, and deployment of production-grade Generative AI workflows and Ontology-driven applications to address high-stakes real-world challenges.
This role operates much like a hands-on AI startup technical leader-taking concepts from problem decomposition, data integration, and prototyping all the way to robust, scalable field deployment leveraging Palantir platforms (AIP, Foundry).
Core Responsibilities
  • Solution Architecture & Platform Delivery: Design, build, optimize, and deploy end-to-end LLM workflows, data pipelines (PySpark/Python), and generative AI tools natively within Palantir AIP (Artificial Intelligence Platform) and Palantir Foundry.
  • Ontology-Grounded AI Workflows: Map complex enterprise domain logic into Palantir Ontologies, connecting unstructured LLM tool-calling and agentic reasoning directly to structured operational datasets and downstream actions.
  • Client & Business Strategy: Partner directly with technical leads and executive stakeholders to translate complex operational challenges into actionable AI implementations and clear business outcomes.
  • Product Feedback Loop: Capture field insights, client requirements, and edge-case operational failures to directly inform and refine internal core AI product platforms, tooling, and reusable Palantir AIP components.
  • Iterative Problem Solving: Work in agile, cross-functional teams to rapidly prototype, validate, and scale production-ready AI solutions and custom user interfaces (e.g., AIP Logic, Workshop, Slate).

Key Qualifications
Required Experience & Technical Skills
  • Palantir Ecosystem Expertise:
    • Proven experience building and deploying applications on Palantir Foundry and/or Palantir AIP.
    • Hands-on experience with Palantir Ontology modeling, AIP Logic, Workshop/Slate frontend design, and data transform pipelines.
  • Gen AI & LLM Engineering:
    • Proven track record of building and deploying solutions utilizing Large Language Models (LLMs), RAG architectures, prompt engineering, and agentic tool-calling frameworks.
  • Machine Learning & Evaluation Fundamentals:
    • Solid grounding in ML core concepts, including evaluation methodologies (evals), guardrails, model fine-tuning, and problem decomposition.
  • Software & Data Engineering Proficiency:
    • Strong coding skills in Python (including PySpark / Spark for high-volume data transforms).
    • Proficiency in additional languages such as TypeScript/JavaScript, Java, or C++.
  • Engineering Background:
    • Bachelor's or Master's degree (or equivalent practical experience) in Computer Science, Software Engineering, Mathematics, Physics, Machine Learning, or a related technical field.
  • Business & Communication Skills:
    • Ability to solve business-oriented operational problems rather than academic benchmarks.
    • Strong client-facing communication skills to bridge technical architectures with executive decision-makers.
  • Willingness to Travel:
    • Ability and willingness to travel to client sites as needed (up to 25%).

Preferred / Bonus Qualifications
  • Experience with cloud infrastructure (AWS, Azure, GCP), containerization (Docker, Kubernetes), and DevOps / CI-CD pipelines.
  • Official Palantir Certifications (Palantir Foundry Data Engineer, Application Developer, or AIP Specialist).
  • Hands-on experience deploying AI systems in high-compliance or complex environments (Federal/Defense, Healthcare, Finance, or Supply Chain).

Apply