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Job Title: AI Consultant \u2013 Manufacturing and Service Lifecycle (SLM)<\/p>\n
Location: USA – CA, Santa Clara
Job Type: Full-Time | Permanent
Shift: General Business Hours
Salary: USD 150000 – 199000
Relocation: Available for qualified candidates
Visa Sponsorship: Available<\/p>\n
Job Summary<\/p>\n
We are seeking an experienced AI Consultant with strong expertise in machine learning, deep learning, and generative AI. This role requires deep domain experience in manufacturing and service lifecycle management, with a focus on automotive, commercial vehicles, and heavy equipment industries.<\/p>\n
The ideal candidate is a full stack AI engineer capable of designing, developing, and deploying AI solutions across product design, production, quality, aftersales, and service operations.<\/p>\n
This position combines technical leadership with consulting responsibilities, including pre-sales discussions, client workshops, prototyping, and solution delivery.<\/p>\n
Key Responsibilities<\/p>\n
1. AI Solutioning and Consulting<\/p>\n
Identify high-value AI use cases in manufacturing and service operations.
Lead pre-sales discussions, client workshops, and AI opportunity assessments.
Build proof-of-concepts, prototypes, and demos to demonstrate value.
Translate business objectives into scalable AI architectures and roadmaps.
2. Technical Leadership<\/p>\n
Design and implement end-to-end AI pipelines for:
Time-series forecasting
Anomaly detection
Computer vision inspection
Document understanding and NLP
Build generative AI applications and agentic AI workflows for manuals, parts lookup, and technician copilots.
Architect RAG-based knowledge assistants trained on service data and technical documentation.
Ensure strong integration across data engineering, modeling, deployment, and optimization.
3. Cloud Engineering and MLOps<\/p>\n
Develop and deploy AI workloads on AWS, Azure, or GCP.
Implement MLOps and LLMOps best practices for model tracking, versioning, automation, and monitoring.
Containerize and deploy workloads using Docker and Kubernetes.
Create and manage APIs using FastAPI or Flask.
Integrate AI solutions with IoT and edge systems for real-time inference.
4. Manufacturing and SLM Domain Expertise<\/p>\n
Apply AI across the product and service lifecycle including:
Digital twins
Defect detection and quality prediction
Process optimization
Predictive maintenance
Spare parts forecasting
Root-cause and warranty analytics
Build GenAI copilots tailored for dealership, service centers, and field technicians.
Enable feedback loops between engineering, production, and service teams.
5. Thought Leadership and Enablement<\/p>\n
Represent the organization in client meetings, RFP responses, and innovation showcases.
Mentor teams in industrial AI, full-stack AI development, and generative AI capabilities.
Support the development of AI accelerators, reference architectures, and reusable assets.
Required Qualifications<\/p>\n
12 to 15 years of experience in AI or machine learning.
Minimum 2 years of experience with generative AI, large language models, or agentic AI.
Strong skills in Python and frameworks such as TensorFlow, PyTorch, Scikit-learn, Hugging Face, and LangChain.
Hands-on experience with AWS, Azure, or GCP.
Experience with Docker, Kubernetes, and API frameworks.
Practical knowledge of MLflow, Azure ML, Vertex AI Pipelines, or Kubeflow.
Strong understanding of manufacturing operations, IoT systems, and service lifecycle data models.
Excellent communication skills with both technical and business stakeholders.
Preferred Qualifications<\/p>\n
Experience with digital twin frameworks or predictive maintenance solutions.
Knowledge of vector databases such as Pinecone, Weaviate, FAISS, or Azure AI Search.
Familiarity with PLM, ERP, and SLM systems such as Windchill, Teamcenter, or SAP.
Background in automotive, heavy equipment, or commercial vehicles.
Certifications in AWS, Azure, or GCP machine learning tracks.
Pay: $150,000.00 – $199,000.00 per year<\/p>\n
Work Location: In person
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