Machine Learning Engineer, Digital Experience
Pure StorageSanta Clara, California
Full Time
Posted September 17, 2026
$180k - $270k
Apply Now
Application opens on company website
Job Description
$180,000
Key Responsibilities
- As a Machine Learning Engineer on the Digital Experience Insights team, you'll help take machine learning models from prototype to production, building the pipelines, infrastructure, and engineering practices that let models run reliably at scale. You'll also build and validate models yourself when needed, but the core of the role is making sure good models actually make it into production and stay healthy once they're there. This role sits within a fast-moving analytics organization where the specific projects shift over time, so we're looking for someone who can adapt their approach to whatever problem is in front of them.
- 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.
- We are primarily an in-office environment and therefore, you will be expected to work from the Santa Clara office in compliance with Everpure's policies, unless you are on PTO, or 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.
- 3-5 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 machine learning and statistical modeling, with familiarity with a library such as Scikit-Learn or PyTorch, and enough grounding to build or extend a model when needed.
- 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.
- #LI-ONSITE
- Salary ranges are determined based on role, level and location. For positions open to candidates in multiple geographical locations, the base salary range is reflective of the labor market across the applicable locations.
- This role may be eligible for incentive pay and/or equity.
- There is no application deadline and we accept applications on an ongoing basis until the job is filled.
Ready to Apply?
Join Pure Storage and make an impact in renewable energy
Stay Updated on Sustainability Jobs
Get the latest renewable energy jobs and career tips delivered to your inbox.
Job Alerts
Get notified about new sustainability jobs
More at Pure Storage
Similar Jobs
Jobs in Santa Clara, California
More jobs at Pure Storage
Similar jobs in Power Generation
Is this your company?Claim your listing — free →