Senior Data Scientist, Production ML & Pipelines

Intetics Inc.; Mountain View (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Intetics Inc. is seeking a Staff Data Scientist / Machine Learning Engineer in Mountain View, CA to design and productionize predictive models and data pipelines.

You will own end-to-end ML workflows, from feature engineering to model deployment, with focus on reliability and scalability. You will work with cross-functional teams to calibrate models, monitor drift, and deliver business-ready signals via robust Python services and cloud-based orchestration.

Qualifications

• 5+ years of hands-on ML engineering in Python with production models.
• Proficient with gradient-boosted trees (XGBoost/CatBoost/LightGBM) in production.
• Strong SQL and BigQuery fluency for crafting feature pipelines.
• GCP production experience with Cloud Run, Airflow, Vertex AI, and Pub/Sub.
• Understanding model calibration and business-value optimization.
• Experience with outbound API integration of model outputs.

Responsibilities

• Design, build, and maintain pLTV models.
• Develop tiered scoring framework for model selection.
• Create calibration frameworks for business-ready outputs.
• Own feature engineering and scalable datasets.
• Monitor performance, drift, and data distribution changes.
• Develop production-grade Python services and data pipelines.
• Implement testing, CI/CD, monitoring, and deployment safeguards.
• Collaborate with stakeholders to improve data quality and scalability.
• Operate ML workflows in cloud environments with orchestration.
• Ensure reliability and impact of ML systems on decisions.

Skills

Python (production)

Gradient-boosted trees

XGBoost

CatBoost

LightGBM

BigQuery

SQL

GCP

Cloud Run

Airflow/Composer

Vertex AI

CI/CD

Docker

Data pipelines

Model calibration

Feature engineering

DevOps for ML

API integration

Tools

Docker

Kubernetes

Airflow

Vertex AI

Pub/Sub

Cloud Run

Job description

Intetics Inc. is seeking a Staff Data Scientist / Machine Learning Engineer in Mountain View, CA to design and productionize predictive models and data pipelines.

You will own end-to-end ML workflows, from feature engineering to model deployment, with focus on reliability and scalability. You will work with cross-functional teams to calibrate models, monitor drift, and deliver business-ready signals via robust Python services and cloud-based orchestration.