ML Infra Engineer: Scalable AI & Cloud Pipelines

Gritt; South San Francisco (CA); On-site; USD 170,000 - 230,000; Full time

Job summary

Gritt is building autonomous robotics and AI-powered infrastructure for construction sites, starting with solar projects. We seek an ML Infrastructure Engineer to architect scalable cloud pipelines that train, validate, and evaluate models for autonomous systems.

You’ll own core data workflows, metrics, and tooling in a fast-paced startup setting. You’ll collaborate across teams to deploy production-quality ML pipelines, optimize GPU usage, and push the boundaries of AI in robotics.

Qualifications

• Degree in computer science or related engineering disciplines (or equivalent experience).
• 4+ years of experience deploying high-performance ML pipelines in production.
• Proficient in Python and comfortable with C++/Go.
• Experience with ML frameworks like PyTorch.
• Experience with IO and data-loading workflows, including Parquet, HDF5, TFRecord etc.
• Experience with deploying on cloud platforms like AWS, GCP or Azure.
• Experience with tooling like Docker, Kubernetes, and Airflow.

Responsibilities

• Develop and deploy scalable AI training and validation pipelines in the cloud.
• Spin up distributed pipelines for data ingestion, pre-processing, training and evaluation.
• Deploy monitoring and CI/CD pipelines.
• Enable large-scale evaluation of AI models via cloud-based metrics.
• Enable large-scale evaluation of autonomy software and models via simulations in the cloud.
• Optimize performance, I/O and GPU utilization.
• Build tooling and dashboards for rapid experimentation, orchestration and visualization.
• Work with other teams to integrate cloud tooling into workflows.

Skills

Python

C++/Go

PyTorch

Cloud platforms

CI/CD

Education

Bachelor's degree in CS or related field

Tools

Docker

Kubernetes

Airflow

Parquet

HDF5

TFRecord

AWS

GCP

Azure

Job description

Gritt is building autonomous robotics and AI-powered infrastructure for construction sites, starting with solar projects. We seek an ML Infrastructure Engineer to architect scalable cloud pipelines that train, validate, and evaluate models for autonomous systems.

You’ll own core data workflows, metrics, and tooling in a fast-paced startup setting. You’ll collaborate across teams to deploy production-quality ML pipelines, optimize GPU usage, and push the boundaries of AI in robotics.