ML Engineer

We supply aluminum plate, bar, and rounds to aerospace and defense manufacturers, but we're much more than a metals company. Every order, machine, and shipment is powered by software that our engineering team builds. Our products manage factory operations, quoting, inventory, scheduling, demand intelligence, and customer experience.

We're looking for an exceptional ML Engineer who wants to build production machine learning systems that directly impact real-world operations. This isn't a research-only role. You'll own models from idea to production, work directly with software engineers and factory operators, and build systems that become core to how the company operates.

If you're someone who enjoys solving difficult real-world problems, thrives in ambiguity, and wants to own products end-to-end, we'd love to talk.

What You'll Do

As an ML Engineer, you'll own the machine learning lifecycle across multiple business-critical systems.

You'll:

• Build production ML systems from concept through deployment, monitoring, and continuous improvement.
• Develop cut-time prediction models based on alloy, thickness, geometry, machine characteristics, and operational data.
• Design nesting optimization and scoring models that continuously improve manufacturing efficiency.
• Build demand intelligence and procurement forecasting models.
• Develop NLP and LLM-powered systems for sales order parsing, RFQ processing, document understanding, and customer communication.
• Build computer vision and OCR solutions for certification processing, dimensional inspection, and quality automation.
• Own the complete ML lifecycle including:
• Data collection
• Data labeling
• Feature engineering
• Model development
• Training
• Evaluation
• Deployment
• Monitoring
• Retraining
• Build scalable feature pipelines and ML infrastructure that enable future machine learning initiatives.
• Work closely with software engineers to integrate ML into our core platforms.
• Spend time on the factory floor with operators, schedulers, buyers, and manufacturing teams to understand the real problems your models solve.
• Continuously improve systems by identifying opportunities to make products smarter, faster, and more reliable.

What We're Looking For

We're looking for engineers who have built and owned production ML systems-not just experimented with models., We're Especially Interested In Candidates Who Have

• Worked at early-stage startups or high-growth technology companies.
• Owned ML products from concept through production.
• Built customer-facing B2B products with measurable business impact.
• Designed production ML architectures rather than only training models.
• Worked directly with product teams, customers, or business stakeholders.
• Demonstrated technical ownership and independent decision-making.
• Shipped multiple production systems and can clearly explain their technical and business impact.
• Thrive in fast-moving environments where engineers wear multiple hats., Successful engineers
• Take ownership of difficult problems without waiting for direction.
• Build production systems that create measurable business value.
• Balance experimentation with pragmatic engineering.
• Work directly with users to understand real operational challenges.
• Think beyond individual models and improve the overall product.
• Continuously raise the technical bar for reliability, scalability, and maintainability.

Why Join our client?

• Own production ML systems that directly impact a real business.
• Work on challenging applied AI problems with immediate real-world feedback.
• Build software that powers manufacturing instead of proof-of-concept demos.
• Join a fast-moving engineering team where ownership matters more than hierarchy.
• Collaborate closely with software engineers, operators, and company leadership.
• Help define the future of AI-powered manufacturing.

Pay: $115,000.00 - $150,000.00 per year

• 5+ years of experience building and shipping production machine learning systems.
• Strong Python skills and experience with modern ML frameworks such as PyTorch, JAX, TensorFlow, or equivalent.
• Demonstrated experience deploying production models that solve real customer or operational problems.
• Experience building APIs and integrating ML into production software.
• Strong understanding of MLOps, model monitoring, retraining strategies, and production operations.
• Experience working with messy real-world datasets, including collecting, cleaning, labeling, and structuring training data.
• Experience using modern AI development tools to improve engineering productivity.
• Strong software engineering fundamentals with the ability to write maintainable production code.
• Excellent problem-solving and communication skills., * Experience in manufacturing, supply chain, logistics, industrial AI, or operations research.
• Computer vision experience including OCR, defect detection, dimensional inspection, or quality systems.
• Experience with optimization algorithms including scheduling, routing, or nesting.
• Production NLP or LLM systems including retrieval, structured extraction, or agentic workflows.
• Experience integrating ML with industrial hardware, PLCs, CNC controllers, or factory systems.
• Contributions to open-source projects, published research, or a portfolio of production systems you've built.

5.05.0 out of 5 stars Michigan $115,000 - $150,000 a year - Full-time