Machine Learning Engineer
Nox Metals
About the role
About Nox Metals. American factories deserve a supply chain that moves as fast as they do. Nox Metals is building it, along with the tools that run it. We’re a technology company with operations in Metro Detroit and Los Angeles, supplying aluminum plate, bar, and rounds to aerospace and defense manufacturers. We use software and automation to supply metal to American factories faster than the industry thought possible.
The role. We’re hiring a Machine Learning Engineer to build production systems that make quoting, material selection, planning, and factory decisions faster and more accurate. You will work with messy operational data, test ideas against real outcomes, and put the useful ones into production.
This is applied ML. A model matters only when it improves a decision, survives real operating conditions, and earns the trust of the people using it.
You will:
Identify high-value opportunities for machine learning and optimization
Build datasets, features, models, evaluation systems, and production pipelines
Establish strong baselines before adding complexity
Deploy models into customer and internal workflows with software engineers
Monitor model quality, drift, latency, and business impact
Design safeguards and clear fallbacks for uncertain predictions
Work with operators and domain experts to understand constraints and failure modes
Improve data quality and make model behavior explainable
Document experiments and communicate tradeoffs clearly
You are:
Strong in applied machine learning, statistics, and software engineering
Comfortable working in Python and SQL
Rigorous about evaluation and skeptical of impressive-looking demos without evidence
Able to turn an operational problem into a measurable learning problem
Comfortable deploying and maintaining models, not just training them
Curious about factories, materials, and supply chains
Clear, practical, and willing to change course when the data disagrees
Nice to have:
Experience with operations research, geometric optimization, forecasting, or pricing
Experience with industrial, logistics, or marketplace data
Experience building human-in-the-loop decision systems
Experience applying modern AI models responsibly in production
Benefits:
Equity in Nox Metals
Company-paid medical, dental, and vision insurance
This role is full time, in person in Los Angeles.
Nox Metals is an equal opportunity employer. We hire based on skill, attitude, and fit for the work, and we do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, height, weight, marital status, or any other protected status under federal, state, or local law.
Responsibilities
- Identify high-value opportunities for machine learning and optimization
- Build datasets, features, models, evaluation systems, and production pipelines
- Deploy models into customer and internal workflows
- Monitor model quality, drift, latency, and business impact
- Design safeguards and fallbacks for uncertain predictions
- Work with operators and domain experts to understand constraints and failure modes
- Improve data quality and make model behavior explainable
- Document experiments and communicate tradeoffs
Qualifications
- Strong applied machine learning, statistics, and software engineering skills
- Comfort with Python and SQL
- Able to evaluate models rigorously and turn operational problems into measurable learning problems
- Experience deploying and maintaining models in production
- Curiosity about factories, materials, and supply chains
- Clear, practical communication and willingness to adapt based on data
- Operations research, geometric optimization, forecasting, pricing, industrial, logistics, marketplace, human-in-the-loop, or production AI experience is a plus
Benefits
- Equity in Nox Metals
- Company-paid medical, dental, and vision insurance