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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML Software Engineer - **Company:** Insight Global - **Location:** Warren, MI, United States - **Experience:** Experienced - **Salary:** $104,000.0 - **Contract:** Permanent contract - **Skills:** Query Performance, A/B Testing, Artificial Intelligence, Systems Engineering, Computer Vision, Nvidia CUDA, Computer Programming, Continuous Integration, Distributed Systems, PostgreSQL, Machine Learning, TypeScript, Supervised Learning, ReactJS, Large Language Models, Backend, Fastapi, Build Management, AI Platforms, Kubernetes, Information Technology, Deployment Automation, Performance Monitor, Machine Learning Operations, Front End Software Development, Software Version Control - **Published:** August 18, 2026 - **Apply:** https://dejobs.org/x/x/272FE3156B51476E9A186994A3B63B19/job/ ## About the Role 3+ years of experience developing AI/ML applications Experience developing an AI application from scratch on a cloud based platform 3 +years of experience programming in python Programming an AI application for manufacturing ## Description We are seeking an experienced AI/ML Engineer with deep expertise in manufacturing systems and production AI to drive the next generation of intelligent manufacturing solutions. In this role, you will be responsible for designing, building, and deploying advanced AI/ML systems specifically tailored for manufacturing operations. You will leverage Domain-Specific LoRA fine-tuning, multi-modal AI models, and enterprise-grade infrastructure to solve complex manufacturing challenges across GM's global production facilities. This role requires hands-on technical execution combined with the ability to architect scalable, production-ready AI solutions that directly impact manufacturing efficiency, quality, and innovation. Success in this role requires a unique blend of AI/ML expertise, manufacturing domain knowledge, and systems engineering excellence. You will work at the intersection of cutting-edge AI technology and real-world manufacturing operations, collaborating with plant engineers, quality teams, robotics specialists, and IT infrastructure teams to digitize Manufacturing. What You'll Do: * Design and implement Domain-Specific LoRA fine-tuning architectures for manufacturing AI applications, including quality inspection, predictive maintenance, process optimization, and robotics control * Develop and deploy multi-modal AI systems that integrate machine vision, controls system, robotics controls, and production telemetry for real-time manufacturing intelligence * Build production-grade ML infrastructure supporting model training, fine-tuning, deployment, and monitoring across distributed manufacturing environments * Architect and develop full-stack AI applications using React/TypeScript frontend with custom state management and FastAPI backend with async patterns and optimized request routing * Implement high-performance database solutions using PostgreSQL with pgvector optimization for embedding storage, query performance tuning, and distributed architectures * Deploy and orchestrate AI services using Kubernetes with service mesh implementation, automated scaling strategies, and comprehensive monitoring and alerting * Develop proprietary embedding models optimized for manufacturing domain knowledge, including defect patterns, assembly sequences, and process parameters * Optimize CUDA kernels and implement parameter-efficient training techniques for large-scale model fine-tuning on manufacturing datasets * Design and build machine vision systems for automated quality inspection, defect detection, and process verification * Train and deploy supervised learning models for robotics control and manufacturing execution system integration, enabling autonomous operations across production lines * Collaborate with cross-functional teams including manufacturing engineers, quality specialists, robotics teams, and plant operations to deliver measurable improvements in production metrics * Establish MLOps best practices including CI/CD pipelines, model versioning, A/B testing, and performance monitoring for manufacturing AI deployments ## Related Videos - [Watch Tests Go Brrrr! : Getting Started with Cypress in ReactJS](https://www.wearedevelopers.com/videos/282-watch-tests-go-brrrr-getting-started-with-cypress-in-reactjs) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Intro to FastAPI](https://www.wearedevelopers.com/videos/462-intro-to-fastapi) - [Developer Experience, Platform Engineering and AI powered Apps](https://www.wearedevelopers.com/videos/990-developer-experience-platform-engineering-and-ai-powered-apps) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [The State of WebDev AI 2025 Results: What Can We Learn?](https://www.wearedevelopers.com/magazine/581-the-state-of-webdev-ai-2025-results-what-can-we-learn) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)