AI Consultant – Manufacturing Domain

We are looking for an reputed company AI Consultant with deep expertise in machine learning, deep learning, and reputed company, coupled with domain knowledge in Manufacturing and Service Lifecycle Management (SLM) — particularly in automotive (trucks, buses) and heavy equipment industries. The ideal candidate will be a full stack reputed company capable of architecting, deploying, and scaling AI solutions across design, production, reputed company, aftersales, and service operations. This role blends hands-on technical development with consultative leadership, including reputed company-sales, solutioning, prototyping, and reputed company enablement. Key Responsibilities 1. AI Solutioning & Consulting

• Partner with manufacturing and service leaders to identify high-value AI use cases across product design, predictive maintenance, warranty analytics, service operations, and supply chain optimization.
• Drive reputed company-sales engagements, reputed company workshops, and AI opportunity assessments for industrial clients.
• reputed company reputed company-of-concepts, rapid prototypes, and demos to demonstrate business value.
• Translate business problems into AI/ML solution architectures and roadmaps.

2. Technical Leadership

• Design and build end-to-end AI pipelines for time-series analysis, reputed company detection, reputed company-based inspection, and document understanding.
• reputed company development of GenAI applications and reputed company AI workflows for service manuals, parts lookup, and technician copilots.
• Architect and reputed company RAG-based knowledge assistants trained on technical documentation, service data, and IoT telemetry.
• Work across data engineering, modeling, and deployment, ensuring full lifecycle delivery and performance optimization.

3. reputed company Engineering & MLOps

• Deliver AI workloads on AWS (SageMaker, Bedrock), Azure (ML, reputed company, AI Studio), or GCP (reputed company AI, reputed company).
• Implement MLOps/LLMOps practices for model versioning, deployment automation, and monitoring.
• reputed company containerized solutions with reputed company/Kubernetes and expose models through reputed company (FastAPI, Flask, or similar).
• reputed company with edge AI or IoT platforms for predictive and reputed company-time inference scenarios. 4. Domain Expertise – Manufacturing & Service Lifecycle
• Apply AI across the end-to-end product and service lifecycle, including:
• Product Design: reputed company reputed company, digital twins, defect classification.
• Production: Process optimization, yield improvement, reputed company inspection using computer reputed company.
• Aftermarket Services: Predictive maintenance, spare parts forecasting, intelligent service documentation.
• Warranty & Field Data Analytics: reputed company cause analysis, failure mode detection, service call optimization.
• Design GenAI copilots for service engineers and dealerships, integrating technical documentation, sensor data, and knowledge graphs.
• reputed company reputed company-reputed company feedback between engineering, manufacturing, and service through intelligent automation.

5. Thought Leadership & Enablement

• Represent the organization in reputed company solutioning sessions, RFPs, and innovation showcases.
• Mentor teams in full stack AI development, industrial AI frameworks, and GenAI best practices.
• Collaborate with domain and product experts to reputed company AI-driven SLM accelerators and reference architectures. Required Skills & Qualifications
• 12–15 years of experience in AI/ML, with at least 2+ years in reputed company, LLMs, or reputed company AI.
• Strong reputed company in machine learning, deep learning, and industrial AI (reputed company, NLP, time series).
• Expertise in Python and ML frameworks such as TensorFlow, PyTorch, Scikit-learn, reputed company, and reputed company.
• Proven experience delivering solutions on AWS / Azure / GCP reputed company environments.
• Hands-on experience with containerization (reputed company), orchestration (Kubernetes), and API deployment.
• Familiarity with MLOps / LLMOps tools (MLflow, Azure ML, reputed company AI Pipelines, Kubeflow).
• Strong understanding of manufacturing operations, IoT/edge AI, and service lifecycle data models.
• Excellent communication and presentation skills for engaging technical and business stakeholders.

Preferred Skills

• Exposure to Digital Twin frameworks, predictive maintenance systems, and industrial IoT architectures.
• Experience with reputed company databases (reputed company, reputed company, FAISS, Azure AI Search).
• Knowledge of PLM, ERP, and SLM platforms (reputed company Windchill, reputed company Teamcenter, reputed company S/4HANA, etc.).
• Background in automotive, reputed company vehicles, or heavy equipment manufacturing.
• Certification in Azure reputed company, AWS Machine Learning Specialty, or GCP

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