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Lorven Technologies Inc.
AI Architect
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What they do
An Artificial Intelligence Engineer develops, tests, and deploys artificial intelligence models. May work closely with data software engineers and data professionals to train and implement AI models into existing systems or develop new applications.
$160,491 / year median in California
Job Description
AI Architect at Lorven Technologies Inc. AI Architect at Lorven Technologies Inc. in Belmont, California Posted in 5 days ago.
Type:
full-timeJob Description:
Our client seeks an AI Architect for a Full Time project in Foster City, CA .Below is the detailed requirementJob Title:
AI Architect Work location :Foster City, CA Duration:
Full Time Job Description:
Bachelor's degree preferably in Computer Science, Information technology, Computer Engineering, or related IT discipline or equivalent experience with 15+ Minimum Experience 6-10 years of experience in AI/ML/Deep Learning model development; 5 years of experience in Cloud AI platforms (AWS SageMaker / AzureML / GCP AI
) 2-3 years hands-on experience with LLMs, NLP, or speech/voice AI systems and deploying AI solutions in production environments 3-5 years of experience designing, training, and fine-tuning LLMs or AI models, Speech/Voice AI systems, Realtime voice pipeline 2+ years of experience in Agentic AI frameworks such as LangChain, LangGraph, A2A, MCP, and Multi agent orchestration 2-3 years of experience Familiarity with model evaluation metrics, bias detection, and optimization 5 years of experience in integrating AI models into applications via APIs or pipelines 3+ years of experience in Python, PyTorch, TensorFlow, or similar frameworks 2-3 years in Azure services- Azure AI Speech & Translator, Azure OpenAI, AI Search, plus Container Apps/AKS, API Management, Event Hubs, Key Vault, and Application Insights Strong mathematical and statistical foundation; Preferred
- Advanced coursework or certifications in ML, DL, or NLP Secondary / Preferred Skills
- Advanced LLM techniques, prompt engineering, and fine-tuning strategies; Continuous learning on emerging AI frameworks and architectures; AI ethics, fairness, and responsible AI deployment; LLMOps
- layered evals (WER, entity