AI Engineer

A t CelLink, we're not using AI just to build better demos, we're using it to solve real manufacturing challenges. As an AI Engineer , you'll turn data from machines, manufacturing systems, quality processes, and engineering teams into AI-powered solutions that improve how we manufacture at scale. That could mean predicting equipment failures before they happen, detecting defects, optimizing processes, improving yield, or building intelligent tools that help engineers make faster, better decisions. The models you build can influence throughput, yield, uptime, quality, equipment reliability, and how quickly our teams solve problems. Essential Duties and Responsibilities Build and deploy AI/ML solutions for manufacturing, quality, equipment reliability, process optimization, anomaly detection, predictive maintenance, defect detection, and engineering productivity. Turn factory data into useful products. Build production-ready models, applications, APIs, and data pipelines using information from manufacturing equipment, MES/ERP, SPC, SCADA, machine vision, databases, and engineering systems. Solve real manufacturing problems. Partner with Manufacturing, Equipment, Process, Quality, Automation & Controls, Software, and other teams to identify high-value opportunities and turn operational challenges into scalable AI solutions. Own the full AI lifecycle from data and experimentation through model training, evaluation, deployment, monitoring, and continuous improvement. Explore what's next. Evaluate and apply machine learning, deep learning, computer vision, generative AI, LLMs, RAG, and AI-enabled workflows where they can create real value. Build responsibly. Design solutions with appropriate controls around accuracy, security, traceability, reliability, and responsible AI use. Work where the problems happen. Collaborate directly with the teams running our manufacturing operation and understand how your solutions perform in the real world. Help establish strong engineering practices around code quality, testing, version control, deployment, documentation, and scalable AI development. Minimum Qualifications Bachelor's degree in Computer Science, AI/ML, Data Science, Software Engineering, Electrical Engineering, Computer Engineering, or a related technical field. 3+ years of professional experience in AI/ML, machine learning, data science, software engineering, or a related technical discipline. Experience developing and deploying AI/ML solutions into production, not just academic or experimental models. Strong Python programming skills. Experience with ML frameworks such as PyTorch, TensorFlow, Scikit-learn, or similar. Working knowledge of SQL, databases, APIs, version control, testing, and software deployment. Strong analytical and problem-solving skills with the ability to work with incomplete, noisy, or rapidly changing data. Ability to take an ambiguous operational problem, break it down, and turn it into a practical technical solution. Strong communication skills and the ability to explain complex AI concepts to both technical and non-technical teams. Preferred Experience AI/ML in manufacturing or other industrial environments Computer vision and automated defect detection Predictive maintenance and equipment reliability Anomaly detection and process optimization Quality prediction and yield improvement Time-series and machine data MES, ERP, SPC, SCADA, historians, or industrial databases Generative AI, LLMs, RAG, vector databases, or AI agents MLOps and production model monitoring Cloud or edge AI deployment Data governance, cybersecurity, or responsible AI Working Conditions / Hours / Physical Requirements Full-time/exempt. This position directly supports an active, high-volume manufacturing environment operating on a 24/7 schedule. The employee’s regular work area may be located on or immediately adjacent to the manufacturing floor. This is not primarily a desk-based position. The employee is expected to spend a significant portion of the workday in production and equipment areas observing operations, evaluating equipment condition, troubleshooting technical issues, engaging with technicians, engineers, operators, and manufacturing leaders, and driving resolution of equipment and process constraints. The employee regularly moves throughout a large manufacturing facility and may stand or walk for extended periods. The position may require climbing stairs, bending, reac