What are the responsibilities and job description for the Artificial Intelligence Data Scientist position at Amor Systems?
Urgent position - AI Data Scientist
#Onsite in Corpus Christi, TX - Experience Required - 15 years
#Onsite in Fort Wayne, IN
Experience required - 10 yrs
Locals preferred for both the locations.
Job Description -
Develop RAG Pipelines :: Design and optimize Retrieval-Augmented Generation (RAG) models to enhance LLM-driven troubleshooting and field operations.
AI Model Development :: Fine-tune and evaluate LLMs (e.g., GPT-4, Llama 3) for task-specific reasoning and accuracy.
Knowledge Integration :: Build high-quality Python code to integrate vector databases (e.g., Pinecone, Milvus, Weaviate) to store and retrieve technical utility documents efficiently.
Operational Intelligence :: Apply LLM solutions to analyze unstructured utility data, such as asset management logs, SCADA alerts, and maintenance records.
Deployment :: Work with software engineers to deploy and scale models in cloud environments (Azure/AWS).
Collaboration: Work cross-functionally with field operations, engineering teams, and stakeholders to understand data needs and deliver solutions.
Required Qualifications
Experience: Professional experience in Data Science/Machine Learning, with at least 1 year focusing specifically on LLMs and Generative AI.
Technical Skills: Advanced proficiency in Python (PyTorch/TensorFlow, LangChain, LlamaIndex) and SQL.
Domain Knowledge: Proven experience in the utility, energy, oil & gas, or heavy industrial sectors.
RAG Expertise: Hands-on experience with vector embeddings, semantic search, and prompt engineering.
Education: Master’s or Ph.D. in Computer Science, Mathematics, Data Science, or a related quantitative field.
Interested candidates please share your resume at hr@amorsystems.com and cc abhinav.amor@gmail.com
#datascientist #AIML #Jobs #RAG #datapipeline #Azure #Aws
#Onsite in Corpus Christi, TX - Experience Required - 15 years
#Onsite in Fort Wayne, IN
Experience required - 10 yrs
Locals preferred for both the locations.
Job Description -
Develop RAG Pipelines :: Design and optimize Retrieval-Augmented Generation (RAG) models to enhance LLM-driven troubleshooting and field operations.
AI Model Development :: Fine-tune and evaluate LLMs (e.g., GPT-4, Llama 3) for task-specific reasoning and accuracy.
Knowledge Integration :: Build high-quality Python code to integrate vector databases (e.g., Pinecone, Milvus, Weaviate) to store and retrieve technical utility documents efficiently.
Operational Intelligence :: Apply LLM solutions to analyze unstructured utility data, such as asset management logs, SCADA alerts, and maintenance records.
Deployment :: Work with software engineers to deploy and scale models in cloud environments (Azure/AWS).
Collaboration: Work cross-functionally with field operations, engineering teams, and stakeholders to understand data needs and deliver solutions.
Required Qualifications
Experience: Professional experience in Data Science/Machine Learning, with at least 1 year focusing specifically on LLMs and Generative AI.
Technical Skills: Advanced proficiency in Python (PyTorch/TensorFlow, LangChain, LlamaIndex) and SQL.
Domain Knowledge: Proven experience in the utility, energy, oil & gas, or heavy industrial sectors.
RAG Expertise: Hands-on experience with vector embeddings, semantic search, and prompt engineering.
Education: Master’s or Ph.D. in Computer Science, Mathematics, Data Science, or a related quantitative field.
Interested candidates please share your resume at hr@amorsystems.com and cc abhinav.amor@gmail.com
#datascientist #AIML #Jobs #RAG #datapipeline #Azure #Aws