Machine Learning Engineer

Build applied machine learning for real engineering problems in KSB GIW’s R&D group. This early-career role blends data foundation work, ML model development (including physics-aware approaches), and user-facing results through visualization and dashboards. The position is based onsite in Grovetown, GA and offers a salary of $80,000 to $120,000 per year (Salary Exempt).

What you’ll work on

• Develop and maintain the data foundation including ingestion, cleaning, transformation, validation, and metadata standards
• Implement and train machine learning models using Python and modern frameworks such as PyTorch
• Contribute to applied AI tooling that supports the broader R&D workflow
• Create visualization and dashboard interfaces that help end users interpret results
• Run experiments, track outcomes, and report findings against defined targets
• Move prototypes toward production quality with testing, documentation, and version control
• Collaborate with engineering disciplines across the team

What you bring

• Bachelor’s degree required; Master’s preferred in Computer Science, Engineering, Applied Math, Physics, or a related field
• 1–3 years of professional or substantial project experience in machine learning, data engineering, or scientific computing
• Strong Python skills with hands-on use of core libraries:
  • PyTorch, scikit-learn for machine learning
  • NumPy, pandas for data work
  • SciPy, Matplotlib for scientific computing
• Foundational understanding of scientific computing including numerical methods, simulation concepts, or modeling of physical systems (essential)
• Foundational understanding of neural networks, model training, and optimization
• Experience with Git and working in a Linux environment
• Strong written and verbal communication skills
• Collaborative, coachable attitude

Helpful experience

• Experience building and maintaining data pipelines, metadata schemas, and data quality frameworks
• Exposure to scientific / physics-informed machine learning such as surrogate modeling or embedding physical constraints into ML models
• Background in CFD, simulation, computational mechanics, or applied physics
• Familiarity with agentic AI / LLM frameworks (LangChain, LangGraph, or similar) enough to collaborate effectively
• Experience with Jupyter, Docker, MLflow, or FastAPI
• Front-end or dashboard experience with React
• Cloud compute experience with AWS or Azure and GPU-based training
• Coursework or research projects in numerical methods, engineering, or applied science

Tools you may use

Python, PyTorch, scikit-learn, NumPy, pandas, SciPy, Matplotlib, Git, Linux, Jupyter, Docker, MLflow, FastAPI, React, LangChain, LangGraph, AWS, Azure.

Additional details

• Department: Engineering, Research & Development
• Reports to: Metallurgical and Materials R&D Lab Manager
• Work location: In person, Grovetown, GA, USA (onsite)
• Shift: First
• FLSA status: Salary Exempt
• Physical requirements: Primarily desk-type duty