Machine Learning Engineer

🏢 Nox Metals · 📍 Los Angeles · 💼 onsite · ⏰ FullTime

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Position Summary & Responsibilities

Machine Learning Engineer | Nox Metals | Los Angeles, CA

About Nox Metals. American factories deserve a supply chain that moves as fast as they do. Nox Metals is building it, along with the tools that run it. We’re a technology company with operations in Metro Detroit and Los Angeles, supplying aluminum plate, bar, and rounds to aerospace and defense manufacturers. We use software and automation to supply metal to American factories faster than the industry thought possible.

The role. We’re hiring a Machine Learning Engineer to build production systems that make quoting, material selection, planning, and factory decisions faster and more accurate. You will work with messy operational data, test ideas against real outcomes, and put the useful ones into production.

This is applied ML. A model matters only when it improves a decision, survives real operating conditions, and earns the trust of the people using it.

You will:

· 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

You are:

· Strong in applied machine learning, statistics, and software engineering

🎯 Candidate Preparation Guide For Nox Metals Applicants

Key Role Competencies & Evaluation Highlights

Key Role Focus:

Measuring industrial supply chain grit, commodities market fluency, and the ability to digitize traditional heavy-industry workflows.

📋 Preparation Priorities (Key Areas to Clarify):

1. Showing impatience or disdain for traditional industry processes and legacy stakeholders
2. Lacking foundational understanding of working capital, inventory, or supply chain risk
3. Proposing purely theoretical software solutions without physical world validation

✨ Recommended Role Alignment Hook:

I bridge the gap between heavy industry supply chains and modern software infrastructure to unlock unprecedented operational leverage.

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