Applied ML Engineer - Factory Optimization (Equity)

Detroit Venture Partners, LLC.; San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Equity in Nox Metals

Company-paid medical, dental, and vesr

Job summary

Nox Metals in Los Angeles is seeking a Machine Learning Engineer to build production systems that speed quoting, material selection, planning, and factory decisions.

You will work with messy operation data, test ideas against real outcomes, and deploy the useful ones into production, ensuring models improve decisions and earn trust.

This is applied ML—focus on impact and measurable results in a manufacturing setting.

Qualifications

• Experience applying machine learning to operational problems.
• Strong statistical thinking and experimental design.
• Proficiency in Python and SQL.
• Ability to deploy and monitor models in production.
• Curiosity about manufacturing, materials, and supply chains.

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.

Skills

Applied ML

Statistics

Software engineering

Python

SQL

Model deployment

Data processing

Job description

Nox Metals in Los Angeles is seeking a Machine Learning Engineer to build production systems that speed quoting, material selection, planning, and factory decisions.

You will work with messy operation data, test ideas against real outcomes, and deploy the useful ones into production, ensuring models improve decisions and earn trust.

This is applied ML—focus on impact and measurable results in a manufacturing setting.