Machine Learning Engineer

In this onsite Machine Learning Engineer role in San Francisco, CA, you will build production machine learning systems that improve speed and accuracy across quoting, material selection, planning, and factory decisions.

Responsibilities

• Find and prioritize high-impact machine learning and optimization opportunities
• Create end-to-end solutions: datasets, features, models, evaluation methods, and production pipelines
• Set strong baseline approaches before introducing additional complexity
• Deploy models into customer and internal workflows in partnership with software engineers
• Continuously monitor model quality, drift, latency, and overall business impact
• Build safeguards and clear fallbacks when predictions are uncertain
• Collaborate with operators and domain experts to understand constraints and failure modes
• Improve data quality and make model behavior more explainable
• Document experiments and communicate tradeoffs clearly

Requirements

• Strong foundation in applied machine learning, statistics, and software engineering
• Practical experience with Python and SQL
• Rigorous about evaluation, skeptical of impressive results without evidence
• Ability to turn an operational problem into a measurable learning objective
• Comfort deploying and maintaining models, not just training them
• Curiosity about factories, materials, and supply chains
• Clear, practical approach and willingness to change direction when data contradicts assumptions

Technology Stack

• 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

Compensation and Benefits

• Salary: USD 151,500 - 167,500 per year
• Equity: Equity in Nox Metals
• Insurance: Company-paid medical, dental, and vision insurance