ML Engineer — Production ML & Data Pipelines

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

Benefits offered by this job

Equity

Flexible time off

Wellness resources

Job summary

Everpure in Santa Clara is seeking a Machine Learning Engineer to join the Digital Experience Insights team. You will take models from prototype to production, building pipelines, infrastructure, and practices that keep models reliable at scale.

You may also build or extend models when needed, working within a fast-moving analytics group. You will collaborate with Data Scientists, Data Engineers, and Software Engineers to translate open-ended business questions into a concrete technical plan and

Qualifications

• Bachelor's/Master's/PhD in CS, Data Science, Engineering, Statistics, or related field or equivalent practical experience.
• 3–5 years of industry experience in data engineering, ML engineering, or hybrid role with production shipping.
• Strong Python/SQL and production-quality code practices.

Responsibilities

• Productionize models from prototype to production with reliable, scalable pipelines for training, serving, and inference.
• Design and maintain data pipelines, feature stores, and workflow orchestration for clean inputs.
• Build monitoring for model performance, data drift, and pipeline health; respond to issues.
• Develop and validate ML models when needed, collaborating with the data science team on design.
• Work with Data Scientists, Data Engineers, and Software Engineers to convert business questions into a concrete technical plan.

Skills

Python

SQL

Airflow

Dagster

Cloud platforms

Communication

Ambiguity management

Education

Bachelor's/Master's/PhD in CS/DS/Engineering/Statistics or related field

Tools

Airflow

Dagster

AWS/GCP/Azure

Scikit-learn

PyTorch

Job description

Everpure in Santa Clara is seeking a Machine Learning Engineer to join the Digital Experience Insights team. You will take models from prototype to production, building pipelines, infrastructure, and practices that keep models reliable at scale.

You may also build or extend models when needed, working within a fast-moving analytics group. You will collaborate with Data Scientists, Data Engineers, and Software Engineers to translate open-ended business questions into a concrete technical plan and