ML Platform Engineer – Production Pipelines for Grid AI

X Development, LLC; Mountain View (CA); Hybrid; USD 166,000 - 244,000; Full time

Benefits offered by this job

Competitive salary and equity

Medical, dental, and vision coverage

Generous PTO and hybrid work model

401(k) with employer contribution

Job summary

Tapestry is seeking an early career machine learning engineer to help build and deploy state-of-the-art ML models for the electric grid. You will collaborate with ML Engineers, Data Scientists, and Software Engineers across multimodal ML domains including information retrieval, NLP, and agentic AI.

You will design and implement scalable ML pipelines, deploy models to production, and containerize training code for cloud execution, partnering with R&D and product teams to deliver impact at scale.

Qualifications

• Master’s or Bachelor’s Degree in Computer Science, Engineering or related field
• 3+ years of professional experience in Software Engineering, DevOps, or Data Engineering with 1–2 years in MLOps or ML infrastructure
• Strong proficiency in Python
• Deep understanding of Docker and basic familiarity with container orchestration
• Experience with public cloud platforms (GCP, AWS, or Azure)
• Experience with version control (Git), CI/CD, and artifact management

Responsibilities

• Design, build, and maintain CI/CD pipelines for ML workflows using tools like Cloud Build or GitHub Actions
• Manage deployment of ML models into production environments (Vertex AI, GKE) focusing on scalability and high availability
• Develop and manage automated ML workflows for training and batch prediction using Vertex AI Pipelines
• Containerize training code (Docker) and optimize for cloud execution, bridging experimentation and production

Skills

Python

Docker

CI/CD

Cloud platforms

Git

ML frameworks

Education

Master’s or Bachelor’s in Computer Science/Engineering

Tools

Vertex AI

Kubernetes

Terraform

Job description

Tapestry is seeking an early career machine learning engineer to help build and deploy state-of-the-art ML models for the electric grid. You will collaborate with ML Engineers, Data Scientists, and Software Engineers across multimodal ML domains including information retrieval, NLP, and agentic AI.

You will design and implement scalable ML pipelines, deploy models to production, and containerize training code for cloud execution, partnering with R&D and product teams to deliver impact at scale.