Senior ML Engineer: Forecasting & AI Agent Automation (GCP)

Quantiphi; Irvine (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Quantiphi seeks a Sr. Machine Learning Engineer with deep data science expertise to support an AI agents engagement for a global technology distributor.

The role emphasizes developing intelligent forecasting models and quotation automation on Google Cloud Platform, blending strong statistical modeling with production ML engineering for operational efficiency. Ideal candidates will demonstrate experience in time-series forecasting, GCP ML stack, and building agentic AI workflows, with a track

Qualifications

• 6+ years of experience in ML engineering and data science with deployed forecasting or predictive models.
• Proficiency in Python (Pandas, NumPy, scikit-learn) and at least one deep learning framework (TensorFlow, PyTorch, or JAX).
• Hands-on experience with GCP ML stack: Vertex AI, BigQuery, Cloud Functions, Cloud Storage, Pub/Sub.
• Strong foundation in statistics, probability, and time-series analysis (ARIMA, Prophet, etc.).
• Experience with AI agent frameworks (LangChain, Vertex AI Agents, etc.).
• Proficiency in SQL for complex analytical queries.
• Experience with MLflow, Vertex AI Experiments, Weights & Biases.

Responsibilities

• Design, develop, and deploy forecasting models for product demand and quotation accuracy using GCP-native services.
• Conduct EDA, feature engineering, and hypothesis testing on distribution & supply chain data.
• Build AI agents for forecasting and quotation workflows with agentic frameworks.
• Develop and maintain production ML pipelines on Vertex AI Pipelines and Cloud Composer.
• Implement experimentation frameworks (A/B testing, causal inference) to validate model improvements.
• Collaborate with data engineering to design feature stores and data pipelines in BigQuery/Cloud Storage.
• Optimize model performance with hyperparameter tuning, cross-validation, ensembling, and interpretability (SHAP, LIME).
• Integrate model outputs into agentic workflows to generate and refine quotations.
• Document architectures, experiments, and agent logic; present findings to stakeholders.
• Contribute to MLOps best practices including model versioning, drift detection, and monitoring.

Skills

Python programming

Statistical modeling

Time-series analysis

SQL

Experiment tracking

MLOps

Education

Bachelor's or Master's in CS/Stats/Math

Tools

Vertex AI

BigQuery

Vertex AI Pipelines

Cloud Composer

LangChain

LlamaIndex

Weights & Biases

MLflow

CrewAI

Job description

Quantiphi seeks a Sr. Machine Learning Engineer with deep data science expertise to support an AI agents engagement for a global technology distributor.

The role emphasizes developing intelligent forecasting models and quotation automation on Google Cloud Platform, blending strong statistical modeling with production ML engineering for operational efficiency. Ideal candidates will demonstrate experience in time-series forecasting, GCP ML stack, and building agentic AI workflows, with a track