Buy aluminum plate and bar cut to size from NOX METALS. Compare 6061, 7075, 7050 and cast tooling plate, then get current pricing and delivery options online. Backed by Y Combinator.
About the role
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. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- 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
More about this role
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 Ferndale, Michigan 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.
· 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,...
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