# Autonomy Engineer - Deep Learning Infrastructure

**Company:** [Skydio](https://hotfix.jobs/companies/skydio)
**Location:** San Mateo, CA
**Role:** ML Engineering
**Salary:** $170k – $237k/yr
**Skills:** MLOps, Deep Learning, Computer Vision, Ml Inference, PyTorch, TensorFlow, Gpu Programming, Kubernetes, Ml Pipelines, Vision Language Models, Edge Deployment, Image Processing, Video Processing
**Posted:** 2025-12-15

> Builds and scales deep learning infrastructure for autonomous drone computer vision workloads, optimizing inference for high throughput/low latency across hardware, and implements MLOps pipelines for model deployment and monitoring. Requires hands-on MLOps, DL/CV expertise, and ML pipeline experience.

## Job Description

## How you'll make an impact
- Develop solutions for high-performance deep learning inference for CV workloads that can deliver high throughput and low latency on different hardware platforms
- Profile CV and Vision Language Models (VLMs) to analyze performance, identify bottlenecks and optimization opportunities and improve power efficiency of deep learning inference workloads
- Design and implement end to end MLOps workflows for model deployment, monitoring and re-training
- Utilize advanced Machine Learning knowledge to leverage training or runtime frameworks or model efficiency tools to improve system performance
- Create new methods for improving training efficiency
- Implement GPU kernels for custom architectures and optimized inference
- Design and implement SDKs that allow customers/external developers to create autonomous workflows using ML
- Leverage your expertise and best-practices to uphold and improve Skydio’s engineering standards

## What makes you a good fit
- Demonstrated hands-on experience with MLOps, ML inference optimization and edge deployment
- Strong knowledge of DL fundamentals, techniques and state-of-the-art DL models/architectures
- Strong fundamentals in CV, image processing and video processing
- Demonstrated hands-on experience building and managing ML pipelines for solving vision or vision language tasks including data preparation, model training, model deployment and monitoring
- Experience and understanding of security and compliance requirements in ML infrastructure
- Experience with ML frameworks and libraries
- Demonstrated ability to take a concept and systematically drive it through the software lifecycle: architecture, development, testing, and deployment, and monitoring
- Comfortable navigating and delivering within a complex codebase
- Strong communication skills and the ability to collaborate effectively at all levels of technical depth

## Compensation
Annual base salary range: $170,000 - $236,500. Equity in the form of stock options, comprehensive benefits including health insurance, paid vacation, sick leave, holiday pay, and 401K.

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