# Autonomy Engineer - Deep Learning Model Acceleration

**Company:** [Skydio](https://hotfix.jobs/companies/skydio)
**Location:** San Mateo, CA
**Role:** ML Engineering
**Salary:** $170k – $278k/yr
**Skills:** Deep Learning, MLOps, Computer Vision, PyTorch, TensorFlow, Gpu Programming, Ml Inference Optimization, Edge Deployment, Vision Language Models, Ml Pipelines
**Posted:** 2025-12-15

> Develops and optimizes deep learning inference infrastructure for real-time computer vision workloads on drones, focusing on high-throughput, low-latency performance across hardware platforms. Builds MLOps workflows, GPU kernels, and SDKs; requires strong DL, CV, and ML pipeline expertise.

## 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 acceleration/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 Machine Learning (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 acceleration/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 - $277,500. Equity in the form of stock options, comprehensive benefits including health insurance, paid vacation, sick leave, holiday pay, and 401K.

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