Autonomy Engineer - ML & DL Infrastructure

Stack

Responsibilities

• ▹Design and implement scalable, interactive data pipelines and annotation workflows
• ▹Build tools leveraging state-of-the-art ML systems for efficient data exploration and curation across the drone fleet
• ▹Design pipelines for data ingestion, versioning, model training, deployment and monitoring
• ▹Optimize and scale deep learning training workflows to improve team iteration velocity
• ▹Uphold and improve Skydio's engineering standards

Requirements

• ▹Demonstrated hands-on experience building large-scale, performant data processing pipelines
• ▹Demonstrated hands-on experience with cloud-based ML platforms, containerization, MLOps platforms and databases
• ▹Understanding of security and compliance requirements in ML infrastructure
• ▹Demonstrated experience building and managing ML pipelines: data prep, training, deployment, monitoring
• ▹Ability to drive a concept through the full software lifecycle: architecture, development, testing, deployment, monitoring
• ▹Comfortable navigating and delivering within a complex codebase
• ▹Strong communication skills, able to collaborate at all levels of technical depth

Nice to have

• ▹Obtaining FAA Part 107 certification within the first 60 days (encouraged, required for certain positions)

Soft skills

What we offer

• ▹Competitive base salary ($170,000-$277,500/year)
• ▹Equity in the form of stock options
• ▹Group health insurance
• ▹Paid vacation, sick leave and holiday pay
• ▹401K savings plan
• ▹Relocation assistance for eligible roles

About the company

Skydio leverages breakthrough AI to create the world's most intelligent flying machines for enterprise, public safety, defense and other customers; learning a semantic and geometric understanding of the world from best-in-class visual data is the core of its autonomy system.