Machine Learning Engineer

NOX METALS
Los Angeles +1 more
On-siteCareer-pivot friendly

Who this role is best for

Geared toward applied machine learning professionals comfortable with deploying models into workflows, working with industrial data, and collaborating closely with domain experts in supply chain and manufacturing.

Best fit for

  • Individuals who have worked with messy operational data and possess a strong understanding of model evaluation and explainability
    — “Work with messy operational data, test ideas against real outcomes”
  • Professionals who are curious about supply chains and have a background in applied ML with a focus on real business impact
    — “A model matters only when it improves a decision, survives real operating conditions, and earns the trust of the people using it”

Things to consider

  • The role demands in-person presence in Los Angeles, which may limit remote flexibility
    — “This role is full time, in person in Los Angeles”
  • There is no explicit seniority requirement, but the role expects a mature understanding of model deployment and production readiness
    — “Deploy models into customer and internal workflows with software engineers”

How to stand out

  • Highlight experience with industrial data and model deployment in your resume and interview responses
    — “Work with messy operational data”
  • Emphasize your ability to improve real-world decisions through ML in your application materials
    — “A model matters only when it improves a decision”
  • Showcase your collaboration with domain experts and your ability to explain complex models clearly
    — “Work with operators and domain experts to understand constraints and failure modes”
  • Demonstrate a track record of establishing strong baselines and evaluating models rigorously
    — “Establish strong baselines before adding complexity”
  • Include examples of designing safeguards and fallbacks for uncertain predictions in your portfolio or resume
    — “Design safeguards and clear fallbacks for uncertain predictions”
Pace · Fast PacedCollaboration · MediumAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • building production systems
  • deploying models into workflows
  • monitoring model quality
Typical background
machine learning experiencesoftware engineering experience

Skills & requirements

Required

Machine LearningData EngineeringSoftware EngineeringModel DeploymentData Quality

Preferred

Operations ResearchGeometric OptimizationForecastingPricing

Stack & domain

Machine LearningOptimizationData AnalysisPythonSQLSoftware EngineeringOperations ResearchGeometric OptimizationForecastingPricingIndustrialLogisticsMarketplaceHuman-in-the-loop Decision SystemsAI ModelsSupply ChainAluminum PlateBarRoundsAerospaceDefenseMetal SupplyFactory DecisionsCuriosityRigorSkepticismCommunicationPracticalityAdaptability

About the role

Original posting from NOX METALS via Ashby

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

· Comfortable working in Python and SQL

· Rigorous about evaluation and skeptical of impressive-looking demos without evidence

· Able to turn an operational problem into a measurable learning problem

· Comfortable deploying and maintaining models, not just training them

· Curious about factories, materials, and supply chains

· Clear, practical, and willing to change course when the data disagrees

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

This role is full time, in person in Los Angeles.

Nox Metals is an equal opportunity employer. We hire based on skill, attitude, and fit for the work, and we do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, height, weight, marital status, or any other protected status under federal, state, or local law.

We will consider for employment qualified applicants with arrest or conviction records in a manner consistent with the Los Angeles Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance, and the California Fair Chance Act.

Source: NOX METALS careers (Ashby)

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