Urgent Need Required Data Scientist ML Architect in SFO, CA

Data Scientist ML Architect – Onsite

SFO, CA

6-12 Months Data Scientist GenAI & Intelligent Automation Role Summary We are seeking a Data Scientist to design, build, and operationalize ML, GenAI, and predictive models that power an enterprise scale AI driven Service Planning & Design (SP&D) platform. The role focuses on cost estimation, calibration, compliance intelligence, and document/image interpretation, working closely with GenAI agents, cloud architects, and domain SMEs. Key Responsibilities Machine Learning & Predictive Modeling Design and develop ML models Build and tune models using XGBoost, Random Forest, scikit learn, and related frameworks Evaluate model performance using MAE, RMSE, R, and error distribution analysis GenAI & Agent Driven AI Collaborate with AI Engineers to embed ML models into GenAI driven, multi agent workflows Work with RAG pipelines for document intelligence and contextual Q&A Enable human readable explanations for predictions and recommendations Data Engineering & Feature Development Analyze structured and unstructured datasets from historical estimates, actual costs, documents, and images Perform feature engineering from: SAP/EES data Historical project attributes Regulatory and standards documentation Ensure data quality, normalization, and anomaly detection Image & Non Text Analytics (Preferred) Support AI image analysis use cases: Classification and attribute extraction from site photos and drawings Compliance signals against engineering standards Collaborate on pipelines using computer vision outputs and ML inference MLOps & Model Lifecycle Support model training, validation, and runtime invocation within cloud native platforms Work with DevOps and AI teams on: Model versioning and reproducibility Monitoring for drift, bias, and performance degradation Provide inputs for MLOps / LLMOps pipelines and governance dashboards Required Skills & Experience Strong foundation in Data Science, Machine Learning, and Statistics Hands on experience with: Python scikit learn, XGBoost Data analysis libraries (NumPy, Pandas) Experience building regression and calibration models Strong understanding of model evaluation metrics Experience working with large, complex enterprise datasets Ability to explain model outputs in business friendly language Preferred Skills Exposure to GenAI / LLM enabled systems Experience with RAG pipelines and vector search concepts Familiarity with computer vision outputs and non text data analysis Experience in utilities, infrastructure, or regulated industries Understanding of AI governance, explainability, and auditability #J-18808-Ljbffr Tech Mirrors