What are the responsibilities and job description for the AI/ML Resource position at Vuesol Technologies Inc?
Title: AI/ML Resource
Location: San Jose, CA (Onsite role)
Qualifications & Skills:
· 3 years of experience in AI/ML, NLP, or Conversational AI development, preferably in financial domains.
· Proficiency in LLM architectures (GPT, Llama, Claude, etc.) and fine-tuning techniques.
· Strong background in Python, TensorFlow, PyTorch, Hugging Face, or similar AI frameworks.
· Experience working with financial datasets, regulatory reporting, or risk analytics.
· Hands-on experience with cloud platforms (AWS, Azure, GCP) for AI model deployment.
· Knowledge of financial domain-specific NLP techniques (e.g., entity recognition, sentiment analysis, text summarization).
· Experience with vector databases, embeddings, and RAG (Retrieval-Augmented Generation) frameworks is a plus.
· Understanding of data security, compliance (e.g., SOX, GDPR), and model interpretability in financial AI applications.
· Prior experience in financial automation, accounting AI tools, or fintech applications.
· Familiarity with LLM Ops, model monitoring, and bias mitigation in AI models.
Location: San Jose, CA (Onsite role)
Qualifications & Skills:
· 3 years of experience in AI/ML, NLP, or Conversational AI development, preferably in financial domains.
· Proficiency in LLM architectures (GPT, Llama, Claude, etc.) and fine-tuning techniques.
· Strong background in Python, TensorFlow, PyTorch, Hugging Face, or similar AI frameworks.
· Experience working with financial datasets, regulatory reporting, or risk analytics.
· Hands-on experience with cloud platforms (AWS, Azure, GCP) for AI model deployment.
· Knowledge of financial domain-specific NLP techniques (e.g., entity recognition, sentiment analysis, text summarization).
· Experience with vector databases, embeddings, and RAG (Retrieval-Augmented Generation) frameworks is a plus.
· Understanding of data security, compliance (e.g., SOX, GDPR), and model interpretability in financial AI applications.
· Prior experience in financial automation, accounting AI tools, or fintech applications.
· Familiarity with LLM Ops, model monitoring, and bias mitigation in AI models.
