AI Engineer - Manufacturing

Role Details Work Type: Direct Hire / Full-Time Experience Required: 10 – 21 Years Compensation: USD 150,000 – 199,000 Per Annum + Bonus up to 20% Eligibility: Green Card Holders, US Citizens, H1B Transfer Travel Requirement: As Required (Client Workshops & Solutioning) Job Overview We are seeking a highly experienced AI Consultant with strong expertise in machine learning, deep learning, generative AI, and agentic AI, backed by robust domain knowledge in Manufacturing & Service Lifecycle Management (SLM). The ideal candidate is a full‑stack AI engineer capable of architecting, developing, and scaling AI solutions across automotive, commercial vehicles, heavy equipment, and industrial manufacturing environments. This role blends hands‑on technical work with consultative leadership, including pre‑sales support, client advisory, PoCs, and end‑to‑end AI solution delivery. Key Responsibilities Identify AI use cases, lead workshops, and design scalable solutions. Build PoCs and prototypes to validate business value. Develop AI pipelines for vision, NLP, and time‑series. Build GenAI apps, agent workflows, and RAG‑based knowledge systems. Own end‑to‑end delivery from data to deployment. Deploy AI solutions on AWS/Azure/GCP. Implement MLOps pipelines, CI/CD, and monitoring. Deploy models via Docker/Kubernetes and APIs. Apply AI to design, production, quality, and service operations. Build predictive maintenance, defect detection, and process optimization solutions. Lead client presentations and innovation demos. Mentor teams and contribute to reusable AI frameworks. Must-Have Qualifications 12–15 years of experience in AI/ML, including 2+ years in Generative AI / LLMs / Agentic AI. Strong expertise in ML, DL, NLP, vision systems, and time‑series modeling. Proficiency in Python and ML frameworks: TensorFlow, PyTorch, Scikit‑learn, Hugging Face, LangChain. Proven cloud delivery experience on AWS / Azure / GCP. Hands‑on experience with Docker, Kubernetes, API deployment. Proficiency in MLOps/LLMOps tools: MLflow, Azure ML, Vertex Pipelines, Kubeflow. Strong knowledge of manufacturing operations, IoT, field service, and SLM data models. Excellent communication & client‑facing skills. Nice-to-Have Qualifications Experience with Digital Twins, Predictive Maintenance, Industrial IoT. Knowledge of vector databases: Pinecone, Weaviate, FAISS, Azure AI Search. Familiarity with PLM/ERP/SLM systems: PTC Windchill, Teamcenter, SAP S/4HANA. Background in automotive, commercial vehicle, or heavy machinery industry. Cloud AI certifications (AWS ML Specialty, Azure AI Engineer, GCP ML Engineer). Seniority Level Mid‑Senior level Employment Type Full‑time Job Function Engineering and Information Technology #J-18808-Ljbffr