ML Engineer

Job description

ML Engineer | Nox Metals | Detroit, MI American factories deserve a supply chain that moves as fast as they do. The next generation of American manufacturing is being built right now. Nox Metals is the supply chain behind it. Nox Metals is a technology company in Detroit 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. We need an ML Engineer to build the intelligence layer of the company. Cut-time models, nesting scoring, demand intelligence, sales order parsing, dimensional vision, cert OCR, and the next ten things we have not built yet. Every machine, every order, every shipment generates data, and you turn it into a moat. Nox Metals is an employer with real opportunity for long term career growth, this is a place to build a career, not just hold a job. You will: - Own ML end to end across applied production work, novel research, and production deployment - Build cut-time models that predict how long every cut takes by alloy, thickness, geometry, and machine - Build nesting scoring and optimization models that make WAYNE smarter every day - Build demand intelligence and procurement models that tell us what to buy, when, and at what price - Build NLP and LLM features for sales order parsing, RFQ ingestion, and customer communication - Build vision and OCR systems for cert package automation and dimensional inspection - Ship features end to end, model, API, UI, deploy, monitor, no handoffs, no waiting - Own the full ML lifecycle, data collection, labeling, training, evaluation, deployment, monitoring, retraining - Build the data infrastructure and feature pipelines that future ML work depends on - Partner with the software team to embed ML into NOX NEST, WAYNE, and Gondor - Walk the floor, talk to operators, schedulers, and buyers, your training data starts where the work happens - Always ask questions, never guess when something is unclear - Look at every system and figure out how to make it better - Work safely every shift and hold your teammates to the same standard You should be: - 5+ years of ML engineering experience shipping production models to real users - Deep technical foundation across applied ML, foundation models or novel architectures, and production deployment - Strong in Python, modern ML frameworks (PyTorch, JAX, or comparable), and the surrounding tooling - Comfortable shipping production code, you build the API, the integration, and the UI when that is what the job needs - Fluent in MLOps, model monitoring, retraining, and the unglamorous work of keeping models alive in production - Experienced collecting, labeling, and structuring training data from messy real-world systems - Cracked with AI tools, modern frameworks, and data, you move 10x faster than engineers who do not - A builder at heart, you would rather ship a working v1 today than ship a perfect v3 next month - High attention to quality, every model, every dataset, every deployment - Always thinking about how to make systems better, you do not accept "this is how we have always done it" - Absolutely customer obsessed, every model eventually shows up as a part on a customer's dock - User obsessed, you sit with the operator, the scheduler, the buyer, you watch them work, and you build models they actually trust - A team player with a good attitude, you make the team better for everyone around you - Someone who takes ownership, if it is in production, it is your responsibility - Precise under pressure and reliable - Organized and detail oriented - Committed to safety, you follow every protocol, wear your PPE, and never cut corners that put people at risk - High agency, you handle big items alone and ask for help when needed - Low ego, you walk the floor, you talk to operators, you do the unglamorous work because it needs to get done - Not afraid to work outside normal hours when America demands it - Never says "that's not my job" Nice to have: - Experience building ML for manufacturing, logistics, supply chain, or industrial environments - Strong vision and CV background, cert OCR, dimensional inspection, defect detection - Strong optimization and operations research background, nesting, scheduling, routing - Strong NLP and LLM background, structured extraction, agentic workflows, applied retrieval - Experience integrating with hardware, PLCs, CNC controllers, or shop floor systems - Open source work, published research, or a portfolio of things you have built This role is full time, in person in Detroit.