Agtonomy

Senior Software Engineer, Machine Learning Infrastructure

Agtonomy

full-time

Posted on:

Origin:  • 🇺🇸 United States • California

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Salary

💰 $160,000 - $220,000 per year

Job Level

Senior

Tech Stack

AWSCloudDockerETLGoogle Cloud PlatformKubernetesPythonTerraform

About the role

  • Architect and build distributed training pipelines that scale to handle petabytes of real-world data from farms, fields, and other rugged environments.
  • Own the ML lifecycle: curate, label, and visualize massive datasets from cameras, LiDAR, and radar to train world-class models.
  • Implement metrics and tags to provide a holistic understanding of model performance and enable the discovery of interesting scenarios for training and evaluation.
  • Create tools to visualize predictions and identify failure cases.
  • Partner with autonomy, platform and cloud engineers to shape models that run flawlessly on real machines in harsh environments.

Requirements

  • A Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related field, plus at least 3 years of experience building systems that matter.
  • Experience with Python, Docker, Kubernetes, and Infrastructure as code (e.g. terraform).
  • Hands-on experience with data pipelines, ETL processes, and distributed computing in cloud environments (AWS, GCP, or similar).
  • A knack for thriving in a fast-paced, collaborative startup where you’ll own big problems and deliver bigger solutions.
  • You’ve wrangled massive datasets and built systems to organize, label, and evaluate them at scale; come with examples!
  • Experience working with data from multiple sensors like cameras, LiDAR, and radar.
  • You’ve benchmarked complex systems or large-scale ML models, finding failure modes and turning them into wins.
  • Familiarity with Nvidia TensorRT or similar tools for optimizing ML inference.