Machine Learning Engineer

NOX METALS is seeking a Machine Learning Engineer (onsite in San Francisco, CA) to build applied machine learning systems that improve quoting, material selection, planning, and factory decision-making.

Responsibilities

• Spot and prioritize high-value opportunities for machine learning and optimization
• Create 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 and track drift, latency, and business impact
• Design safeguards and define clear fallback paths when predictions are uncertain
• Collaborate 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

• Strong foundation in applied machine learning, statistics, and software engineering
• Comfortable working with Python and SQL
• Rigorous approach to evaluation; skeptical of impressive-looking demos without evidence
• Ability to translate an operational problem into a measurable learning problem
• Comfort deploying and maintaining models, not only training them
• Curiosity about factories, materials, and supply chains
• Practical mindset with willingness to change course when the data contradicts assumptions

Technologies

• Python
• SQL

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

Compensation: USD 151,500 - 167,500 per year

Location: San Francisco, CA (onsite)