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Physics Informed Machine Learning Jobs in Northfield, MN

Thomson Reuters

Lead Data Engineer

Eagan, MN · On-site

$116.80K - $140.20K/yr

... data-informed strategies. * Champion and implement advanced AI and machine learning techniques to innovate reporting solutions and provide predictive and prescriptive insights. * Conduct in-depth ...

THOMSON REUTERS

Lead Data Engineer

Eagan, MN · Hybrid

$116.80K - $140.20K/yr

... data-informed strategies. * Champion and implement advanced AI and machine learning techniques to innovate reporting solutions and provide predictive and prescriptive insights. * Conduct in-depth ...

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$5

$21

$26

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

As of May 30, 2026, the average hourly pay for physics informed machine learning in Northfield, MN is $21.09, according to ZipRecruiter salary data. Most workers in this role earn between $13.12 and $26.78 per hour, depending on experience, location, and employer.

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 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.
More about Physics Informed Machine Learning jobs
What cities near Northfield, MN are hiring for Physics Informed Machine Learning jobs? Cities near Northfield, MN with the most Physics Informed Machine Learning job openings:
Physics Informed Machine Learning jobs near you
AI Solution Analyst/Developer

AI Solution Analyst/Developer

Hearth & Home Technologies, LLC

Lakeville, MN • On-site

$65K - $82.50K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Hearth & Home Technologies rating

7.8

Company rating: 7.8 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

Job description

Hearth & Home Technologies is looking for an AI Solutions Analyst/Developer to join our team in Lakeville, MN. This is an on-site role in Lakeville, MN. We are the nation’s leading manufacturer and supplier of hearth products, including a wide variety of gas, electric, wood and pellet burning fireplaces, inserts, stoves, and accessories. Headquartered in Lakeville, Minnesota, with distribution around the world, our innovative culture is supported by a business unit structure that allows us to develop and market products with a strong focus on customers’ needs.  Since 1996, we’ve been dedicated to connecting people through the warmth and comfort of our hearth products.    
We are not accepting any candidates that require company sponsorship to legally work in the United States. No agency candidates.  
 
This role is ideal for someone with an interest in machine learning, generative AI, and applied large language model (LLM) engineering—using today's leading platforms such as Anthropic Claude, OpenAI GPT, Google Gemini, Meta Llama, Mistral, and open-source ecosystems like Hugging Face—to build agentic, multimodal, and retrieval-augmented solutions that deliver measurable value to the business. 
 
Responsibilities
  • Develop, test, and deploy generative AI solutions across text, image, audio, and video modalities, including agentic workflows that plan and execute multi-step tasks.
  • Build and integrate retrieval-augmented generation (RAG) pipelines using modern vector databases, knowledge graphs, and orchestration frameworks such as LangChain / LangGraph, Neo4J, MongoDB.
  • Experiment with and evaluate frontier LLMs—including Anthropic Claude, OpenAI GPT, Google Gemini, and Mistral—through enterprise platforms like Azure AI Foundry.
  • Collaborate with AI developers, data engineers, and business stakeholders to translate requirements into production-ready solutions integrated with HNI systems.
  • Contribute to responsible AI practices aligned with the NIST AI Risk Management Framework, including prompt safety, PII handling, bias testing, and human-in-the-loop review.
  • Use AI-assisted developer tooling (e.g., Claude Code, GitHub Copilot, Cursor) to accelerate delivery, and the Model Context Protocol (MCP) to connect agents to enterprise data and tools.
  • Document and present results, trade-offs, and business insights from generative AI projects to technical and executive audiences.
  • Manage your own project workload, including sequencing, progress tracking, and clear status communication to non‑technical stakeholders.
  • Communicate tradeoffs, limitations, and solution options in plain language to help the business make informed decisions.
  • Develop working knowledge of the hearth industry and HHT’s business so technical decisions reflect real‑world constraints and opportunities.
  • Stay current on applied AI development approaches and bring relevant ideas to the Innovation team  
Qualifications
  • Bachelor's degree (or equivalent) in computer science, software engineering, data science, mathematics, or a related field.
  • Experience, coursework, or demonstrated interest in generative AI models and platforms such as Anthropic Claude, OpenAI GPT, Google Gemini, Meta Llama, Mistral, Hugging Face, and image/video/audio models (DALL·E, Stable Diffusion, Imagen, Veo, ElevenLabs). 
  • Proficiency in Python, with familiarity in at least one additional language (e.g., TypeScript/JavaScript, Java, C#, SQL).
  • Working understanding of machine learning, deep learning, and generative AI concepts—especially LLMs, embeddings, RAG, tool-use / agents, fine-tuning vs. prompting, and evaluation methods for non-deterministic systems.
  • Exposure to cloud AI services on Azure, AWS, or Google Cloud, and interest in enterprise platforms such as Azure AI Foundry, AWS Bedrock, Vertex AI, Databricks, or NVIDIA NIM.
  • Familiarity with version control (Git), APIs, and modern software engineering practices; exposure to containers (Docker), CI/CD, or MLOps tooling is a plus.
  • Awareness of responsible AI topics—data privacy, security, bias, hallucination mitigation, and governance frameworks such as the NIST AI RMF.
  • Ability to work both independently and collaboratively in a cross-functional team environment.
  • Excellent written and verbal communication skills, with the ability to translate technical concepts for business audiences, plus strong analytical and problem-solving skills.