Production ML Engineer — Digital Experience

purestorage; Santa Clara (CA); On-site; USD 180,000 - 270,000; Full time

Benefits offered by this job

Flexible time off

Wellness resources

Team events

Job summary

Everpure in Santa Clara is seeking a Machine Learning Engineer to move ML models from prototype to production, building reliable pipelines for training, serving, and inference. You will design data pipelines, feature stores, and orchestration to ensure clean, timely inputs and healthy deployments.

The role requires 3–5 years in data/ML engineering, strong Python/SQL, experience with Airflow or Dagster, and cloud experience (AWS/GCP/Azure).

Qualifications

• Bachelor's, Master's, or Ph.D. in Computer Science, Data Science, Engineering, Statistics, or a related field, or equivalent practical experience.
• 3-5 years of industry experience in data engineering, ML engineering, or a hybrid data science/engineering role, with a track record of shipping models to production.
• Strong software engineering fundamentals in Python and SQL, including writing production-quality, well-tested code.
• Hands-on experience with a workflow orchestration tool, such as Airflow or Dagster.
• Experience working in a cloud-native environment (AWS, GCP, or Azure). Working knowledge of ML libraries such as Scikit-Learn or PyTorch.
• Good communication skills, with the ability to explain technical work clearly to non-technical stakeholders.
• Comfort working through ambiguity and shifting priorities, and a collaborative approach to working across teams.

Responsibilities

• Productionization: Take models from prototype to production, building reliable, scalable pipelines for training, serving, and inference.
• Data & ML Infrastructure: Design and maintain data pipelines, feature stores, and workflow orchestration so models have clean, timely, well-tested inputs.
• Monitoring & Reliability: Build monitoring for model performance, data drift, and pipeline health, and respond when something breaks.
• Model Development: Build and validate machine learning models and statistical approaches when needed, working closely with the broader data science team on model design.
• Cross-Functional Collaboration: Work with Data Scientists, Data Engineers, and Software Engineers to turn open-ended business questions into a clear technical plan and a working production system.

Education

Bachelor's, Master's, or Ph.D. in Computer Science, Data Science, Engineering, Statistics, or a related field

Tools

Airflow

Dagster

AWS/GCP/Azure

PyTorch

Scikit-Learn

Python

SQL

Job description

Everpure in Santa Clara is seeking a Machine Learning Engineer to move ML models from prototype to production, building reliable pipelines for training, serving, and inference. You will design data pipelines, feature stores, and orchestration to ensure clean, timely inputs and healthy deployments.

The role requires 3–5 years in data/ML engineering, strong Python/SQL, experience with Airflow or Dagster, and cloud experience (AWS/GCP/Azure).