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AI Architect

Job in Torrance, Los Angeles County, California, 90501, USA
Listing for: Yochana
Full Time position
Listed on 2026-07-01
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Cloud Computing: Infrastructure & Operations
Job Description & How to Apply Below

AI Architect

Location:

Torrance, CA

Experience:

10+ years overall experience, with 5+ years in AI/ML and GenAI architecture and implementation, and strong cloud-native delivery experience

Role Summary

The AI Architect will be responsible for designing, architecting, and implementing large-scale AI solutions for Automotive and Manufacturing enterprises, leveraging modern cloud platforms and AI technologies.

This role demands strong hands-on experience in AI/ML, GenAI, data platforms, and MLOps, along with deep understanding of manufacturing and automotive business processes such as smart factories, predictive maintenance, quality analytics, connected vehicles, and supply chain optimization.

The architect will act as a technical leader, working across business stakeholders, solution teams, and cloud platforms to deliver production-grade, scalable AI solutions.

Key Responsibilities
  • AI Architecture & Solution Design
    • Design end-to-end AI / ML / GenAI architectures for Automotive and Manufacturing use cases
    • Define cloud-native reference architectures for AI workloads on AWS, Azure, or GCP
    • Translate business requirements into secure, scalable, and cost-optimized AI solutions
    • Align AI architectures with enterprise security, compliance, and governance standards
  • AI / ML / GenAI Implementation
    • Lead hands-on implementation of AI solutions, including:
      • Machine Learning and Deep Learning models
      • GenAI solutions using LLMs (RAG, embeddings, prompt engineering)
      • Computer Vision and NLP use cases relevant to manufacturing and automotive
      • Ensure transition from POC → Pilot → Production
      • Build and deploy AI pipelines for training, inference, and monitoring
  • Automotive & Manufacturing Use Cases
    • Design and deliver AI solutions for:
      • Predictive maintenance and asset health monitoring
      • Quality inspection using computer vision
      • Smart manufacturing / Industry 4.0 initiatives
      • Supply chain optimization and demand forecasting
      • Connected vehicle and telematics analytics
      • Warranty analytics and root-cause analysis
      • Work with plant, operations, and engineering teams to align AI solutions with real-world workflows
  • Cloud & Platform Engineering
    • Architect AI platforms on:
      • AWS (Sage Maker, Bedrock, EKS, Lambda, S3)
      • Azure (Azure ML, Azure OpenAI, Synapse, Data Factory)
      • GCP (Vertex AI, Big Query, Cloud Run)
      • Design containerized and microservices-based AI systems
      • Implement integrations with enterprise systems (ERP, MES, PLM, IoT platforms)
  • MLOps, Governance & Scalability
    • Establish MLOps frameworks for CI/CD, model versioning, deployment, and retraining
    • Implement monitoring for:
      • Model performance and drift
      • Data quality and pipeline health
      • Cost and usage optimization
    • Ensure AI solutions comply with responsible AI, explainability, and regulatory requirements
Required Skills & Experience
  • AI / Data Technologies
    • Strong expertise in:
      Machine Learning, Deep Learning, NLP
    • GenAI and LLM architectures (RAG, vector search)
    • Hands-on experience with:
      Tensor Flow, PyTorch, Scikit-learn
    • Lang Chain / Llama Index (preferred)
    • Vector databases (Pinecone, FAISS, Milvus)
  • Cloud & Engineering
    • Strong experience in at least one major cloud platform
    • Solid programming skills in Python (mandatory)
    • Experience with: REST APIs, event-driven architectures
    • Docker, Kubernetes
    • Infrastructure as Code (Terraform / ARM / Cloud Formation)
  • Domain Experience (Mandatory)
    • Proven experience delivering AI solutions for:
      Automotive
    • Manufacturing / Industrial enterprises
    • Strong understanding of plant operations, engineering data, and operational KPIs
  • Nice to Have
    • Experience in global, multi-vendor enterprise programs
    • Exposure to IoT platforms and streaming data
    • Cloud and AI certifications (AWS / Azure / GCP)
    • Experience in AMS / Support platforms or operational analytics
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