ML Infrastructure Engineer — Scale ML for Drones (Equity)

Zipline; South San Francisco (CA); On-site; USD 190,000 - 250,000; Full time

Benefits offered by this job

Equity compensation

Discretionary bonuses

Medical, dental, vision insurance

Paid time off

Job summary

Zipline is seeking an ML Training & Inference Infrastructure Engineer as part of the Data Platform team. You will build and scale systems powering our data flywheel and work at the intersection of autonomy and infrastructure to make ML development faster, reproducible, observable, and safe.

This is a strong software engineering role focused on data ingestion, processing pipelines, dataset management, distributed training, continuous model integration, evaluation, and deployment.

Qualifications

• 3+ years of professional software engineering experience, ideally including ML infrastructure, data infrastructure, robotics, autonomy, aerospace, medical devices, or another safety-critical hardware/product environment.
• Strong software engineering practices in Python in a production setting; comfort designing APIs, services, schemas, jobs, and operational workflows.
• Experience building reproducible data pipelines and machine-learning pipelines.
• Experience monitoring data statistics, system performance metrics, pipeline failures, and model/evaluation signals.
• Working knowledge of ML concepts such as datasets, training, evaluation, optimization, statistics, and modern deep learning workflows.

Responsibilities

• Build and operate software infrastructure that enables learning algorithms to leverage Zipline’s large-scale fleet data.
• Design scalable, maintainable data and ML infrastructure for autonomy teams, including dataset creation, validation, training, evaluation, and deployment.
• Own and improve data pipelines that feed into the ML development loop.
• Identify and mitigate bottlenecks in the ML development cycle, especially around orchestration, performance, and reproducibility to increase the rate at which we can improve and scale the delivery experience.

Skills

Python

ML infra

Kubernetes

Cloud AWS

Data pipelines

PyTorch

Tools

APIs

Terraform

Job description

Zipline is seeking an ML Training & Inference Infrastructure Engineer as part of the Data Platform team. You will build and scale systems powering our data flywheel and work at the intersection of autonomy and infrastructure to make ML development faster, reproducible, observable, and safe.

This is a strong software engineering role focused on data ingestion, processing pipelines, dataset management, distributed training, continuous model integration, evaluation, and deployment.