Machine Learning Engineer

Nox Metals is hiring a Machine Learning Engineer in Los Angeles, CA (onsite) to build applied machine learning systems that help improve how the business makes decisions. The focus is on moving from messy operational data to production-ready models that support quoting, material selection, planning, and factory decision-making, with clear evaluation in real operating conditions.

You will partner with software engineers to deploy models into customer and internal workflows, then stay involved after launch through monitoring, safeguards, and measurable impact. The role emphasizes building reliable systems, not just impressive prototypes.

Responsibilities

• 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

Requirements

• Applied machine learning, statistics, and software engineering strength
• Comfortable working in Python and SQL
• Rigorous about evaluation, with skepticism toward impressive-looking demos without evidence
• Ability to convert an operational problem into a measurable learning problem
• Comfort deploying and maintaining models, not only training them
• Curiosity about factories, materials, and supply chains
• Clear, practical approach and willingness to change course when data disagrees

Technologies

• Python
• SQL

Benefits

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

Salary: USD 151,724 - 167,695 per year

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