Machine Learning Engineer

Nox Metals (Los Angeles, CA, onsite) is hiring a Machine Learning Engineer to turn messy operational data into applied production systems that improve quoting, material selection, planning, and factory decision-making.

Responsibilities

• Find and prioritize high-value use cases for machine learning and optimization
• Build end-to-end solutions: datasets, features, models, evaluation systems, and production pipelines
• Start with strong baselines before introducing added complexity
• Deploy models into customer and internal workflows in partnership with software engineers
• Monitor model quality, drift, latency, and business impact after release
• Design safeguards and clear fallback behavior for uncertain or low-confidence predictions
• Partner with operators and domain experts to understand constraints, failure modes, and real-world limits
• Improve data quality and make model behavior more explainable
• Document experiments and communicate tradeoffs clearly

Requirements

• Strong background in applied machine learning, statistics, and software engineering
• Comfortable using Python and SQL
• Rigorous about evaluation; cautious about impressive results without evidence
• Ability to convert an operational challenge into a measurable machine learning problem
• Experience deploying and maintaining models, not only training
• Curiosity about factories, materials, and supply chains
• Clear, practical judgment and willingness to change direction when data contradicts assumptions

Technologies

• Python
• SQL

Salary

• USD 151,724 - 167,695 per year

Benefits

• Equity in Nox Metals
• Company-paid medical, dental, and vision insurance

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