Lead AI Engineer – Manufacturing & Generative AI

Job Summary

We are seeking an experienced Lead AI Engineer to design, develop, and deploy AI-powered solutions for manufacturing and industrial products. The ideal candidate will have strong expertise in Machine Learning, Deep Learning, Generative AI, LLMs, and MLOps, with hands-on experience building scalable AI applications from data ingestion through production deployment. This role requires technical leadership, cross-functional collaboration, and mentoring of junior engineers while delivering enterprise-grade AI solutions.

Key Responsibilities

• Design and implement AI/ML solutions for automation, predictive maintenance, process optimization, and industrial analytics.
• Build and maintain scalable ML pipelines covering data processing, model training, deployment, monitoring, and optimization.
• Develop Generative AI solutions using LLMs, RAG, prompt engineering, transformers, and vector databases.
• Integrate AI capabilities into enterprise applications and manufacturing platforms.
• Deploy and manage production AI models following MLOps best practices, including CI/CD, model monitoring, and version control.
• Collaborate with Product, Engineering, and Manufacturing teams to deliver business-focused AI solutions.
• Mentor junior engineers and promote engineering excellence through code reviews and best practices.
• Stay current with emerging AI technologies and recommend innovative solutions for manufacturing use cases.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• 5–10 years of hands-on experience in AI/ML Engineering, preferably within manufacturing, industrial automation, SaaS, or product companies.
• Strong expertise in Machine Learning, Deep Learning, NLP, Generative AI, LLMs, and RAG.
• Hands-on experience with Python, TensorFlow, PyTorch, Hugging Face Transformers, and model fine-tuning.
• Experience with vector databases, prompt engineering, and AI model deployment.
• Familiarity with AWS, Azure, or GCP, Docker, Kubernetes, Git, and MLOps practices.
• Strong analytical, communication, and problem-solving skills with the ability to work in cross-functional teams.

Preferred Qualifications

• Experience with Digital Twin technologies such as NVIDIA Omniverse, Siemens, or PTC.
• Knowledge of Industrial IoT, PLCs, MES, ERP integration, and manufacturing data systems.
• Experience with Java, Go, or Scala is an added advantage.
• Open-source contributions, research publications, or a Master's degree are preferred.