Machine Learning Engineer, Digital Experience

You will join the Machine Learning Engineer role on the Digital Experience Insights team at Everpure, helping advance machine learning work from early prototypes into dependable production systems. The focus of this position is building the pipelines, infrastructure, and engineering practices that keep models reliable over time.

Role Summary

As a Machine Learning Engineer, you will take machine learning models from prototype to production by building pipelines, infrastructure, and engineering practices. When needed, you will also build and validate models, with an emphasis on ensuring models make it into production and remain healthy after deployment.

Responsibilities

• Move machine learning models from prototype to production by building reliable, scalable pipelines for training, serving, and inference.
• Design and maintain data pipelines, feature stores, and workflow orchestration to ensure models receive clean, timely, and well-tested inputs.
• Implement monitoring for model performance, data drift, and pipeline health, and take action when issues arise.
• Build and validate machine learning models and statistical approaches as needed, partnering with the broader data science team on model design.
• Collaborate with Data Scientists, Data Engineers, and Software Engineers to translate open-ended business questions into a clear technical plan and a functioning production system.
• Work primarily from the Santa Clara office (onsite) in accordance with Everpure policies, unless on PTO, work travel, or other approved leave.

Requirements

• Bachelor’s, Master’s, or Ph.D. in Computer Science, Data Science, Engineering, Statistics, or a related field, or equivalent practical experience.
• 3 to 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 the ability to write 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 such as AWS, GCP, or Azure.
• Working knowledge of machine learning and statistical modeling, with familiarity in libraries such as Scikit-Learn or PyTorch, and enough grounding to build or extend models when needed.
• Good communication skills, including the ability to explain technical work clearly to non-technical stakeholders.
• Comfort operating through ambiguity and shifting priorities, with a collaborative approach across teams.

Technologies

• Python
• SQL
• Airflow
• Dagster
• AWS
• GCP
• Azure
• Scikit-Learn
• PyTorch

Location and Compensation

• Location: Santa Clara, CA (onsite)
• Salary: USD 180,000 to 270,000 per year

What You Can Expect From Everpure

• Innovation: A culture that supports critical thinking, taking on challenges, and aiming to be a trailblazer.
• Growth: Support to grow and contribute to meaningful work.
• Team: A collaborative environment focused on building each other up and setting aside ego for the greater good.
• Perks and balance: Flexible time off, wellness resources, and company-sponsored team events.
• Accommodation: Candidates with disabilities may request accommodations for all aspects of the hiring process by contacting [email protected] if invited to an interview.
• Equal opportunity: Everpure is proud to be an equal opportunity employer.