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AI Architectcont

Job in Torrance, Los Angeles County, California, 90501, USA
Listing for: Cynet Systems
Full Time position
Listed on 2026-06-27
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 75 - 80 USD Hourly USD 75.00 80.00 HOUR
Job Description & How to Apply Below

AI/ML Solutions Architect

Pay Range: $75hr - $80hr

Requirement/Must Have:
  • 10+ years of overall IT experience.
  • 5+ years of experience in AI/ML and Generative AI architecture and implementation.
  • Strong experience with cloud-native AI solution delivery.
  • Hands-on expertise in Machine Learning, Deep Learning, NLP, and Generative AI technologies.
  • Strong programming experience with Python.
  • Experience with Tensor Flow, PyTorch, and Scikit-learn.
  • Experience designing and implementing GenAI and LLM-based architectures including RAG, vector search, embeddings, and prompt engineering.
  • Strong experience with at least one major cloud platform such as AWS, Azure, or GCP.
  • Experience with Docker, Kubernetes, REST APIs, and event-driven architectures.
  • Experience implementing MLOps frameworks and AI governance processes.
  • Proven experience delivering AI solutions within Automotive and Manufacturing industries.
  • Strong understanding of plant operations, engineering data, and operational KPIs.
Experience:
  • Experience designing end-to-end AI, ML, and GenAI architectures.
  • Experience implementing scalable AI platforms and cloud-native AI workloads.
  • Experience transitioning AI solutions from proof of concept to production.
  • Experience building AI pipelines for model training, deployment, inference, and monitoring.
  • Experience integrating AI systems with ERP, MES, PLM, and IoT platforms.
  • Experience with predictive maintenance, quality inspection, smart manufacturing, and connected vehicle analytics.
  • Experience implementing monitoring for model drift, data quality, and operational performance.
  • Experience with Infrastructure as Code tools such as Terraform, ARM, or Cloud Formation.
  • Experience working within enterprise-scale and multi-vendor environments.
Responsibilities:
  • Design end-to-end AI, ML, and Generative AI architectures for Automotive and Manufacturing use cases.
  • Define secure, scalable, and cost-optimized cloud-native AI reference architectures.
  • Lead implementation of machine learning, deep learning, NLP, and GenAI solutions.
  • Build and deploy AI pipelines for training, inference, retraining, and monitoring.
  • Design AI solutions for predictive maintenance, quality analytics, supply chain optimization, and connected vehicle use cases.
  • Develop AI-powered computer vision and NLP solutions for manufacturing operations.
  • Collaborate with plant, engineering, and operations teams to align AI solutions with business workflows.
  • Architect AI platforms using AWS, Azure, or GCP services.
  • Implement containerized and microservices-based AI systems.
  • Establish MLOps frameworks for CI/CD, model versioning, deployment, and governance.
  • Monitor model performance, pipeline health, data quality, and operational efficiency.
  • Ensure compliance with responsible AI, explainability, security, and governance standards.
  • Provide technical leadership and guidance across AI delivery initiatives.
Should Have:
  • Experience with Lang Chain or Llama Index.
  • Experience with vector databases such as Pinecone, FAISS, or Milvus.
  • Exposure to IoT platforms and streaming data architectures.
  • Experience in operational analytics or AMS/support platforms.
  • Cloud and AI certifications from AWS, Azure, or GCP.
  • Experience working in global enterprise transformation programs.
Skills:
  • Artificial Intelligence.
  • Machine Learning.
  • Deep Learning.
  • Natural Language Processing.
  • Generative AI.
  • Large Language Models.
  • Retrieval-Augmented Generation.
  • Prompt Engineering.
  • Vector Search.
  • Tensor Flow.
  • PyTorch.
  • Scikit-learn.
  • Lang Chain.
  • Llama Index.
  • Pinecone.
  • FAISS.
  • Milvus.
  • Python.
  • AWS Sage Maker.
  • AWS Bedrock.
  • Azure ML.
  • Azure OpenAI.
  • Vertex AI.
  • Big Query.
  • Docker.
  • Kubernetes.
  • REST APIs.
  • Event-Driven Architecture.
  • Terraform.
  • ARM Templates.
  • Cloud Formation.
  • MLOps.
  • CI/CD.
  • Model Monitoring.
  • Data Governance.
  • Computer Vision.
  • Cloud-Native Architecture.
Qualification and

Education:
  • Bachelor’s degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related field.
  • Master’s degree preferred.
  • Relevant cloud and AI certifications are a plus.
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