Skydio
Defense · Autonomous drones (civilian + defense)
- HQ
- Redwood City, US
- Founded
- 2014
- Website
- skydio.com
Currently tracking 18 active AI roles, with 39 new openings in the last 4 weeks. Primary focus: Serve · Engineering. Salary range $47k–$278k (avg $195k).
Skydio has 21 active AI-related job listings. The company's hiring is distributed across several stages, with "serving infrastructure" and "post-training" each accounting for 24% of the roles, followed by "application" and "agents" at 19% each. Engineering roles are the most frequent, representing 19 of the total positions. Skydio is primarily hiring in the United States and Switzerland. Frequent tech tags include model_serving, inference_infra, embodied_ai, synthetic_data, and fine_tuning, suggesting a focus on deploying and optimizing AI models for real-world applications. In the last 30 days, Skydio posted 1 new AI role, a decrease from the previous 30-day period.
Defense · Autonomous drones (civilian + defense)
Skydio currently has 28 active AI-related roles in our index. The most common open titles are: Autonomy Engineer - Deep Learning (2), Autonomy Engineer - Deep Learning Infrastructure (2), Autonomy Engineer - Deep Learning Model Acceleration (2), Autonomy Engineer - ML & DL Infrastructure (2), Autonomy Engineer Intern - Computer Vision/Deep Learning Fall 2026 (2). Most positions are in Engineering and Research.
Skydio's active AI hiring is concentrated in: agents (29%), application (21%), serving infrastructure (21%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Skydio is hiring AI talent in: United States (16 roles), Switzerland (11 roles).
Job postings at Skydio most frequently reference: model serving, inference infra, embodied ai, multimodal, vision.
In the past 30 days, Skydio has posted 4 new AI-related roles. That is a -67% change versus the prior 30 days (12 → 4).
| Title | Stage | AI score |
|---|---|---|
| Senior Autonomy Engineer - Deep Learning Senior Autonomy Engineer focused on designing, implementing, and optimizing deep learning models for real-time object detection, tracking, segmentation, and optical flow estimation on Skydio drones. The role involves leveraging state-of-the-art methods, curating synthetic and real-world data, and refining models for low-latency embedded hardware, with a strong emphasis on computer vision and robotics. | ServeData | 9 |
| Autonomy Engineer - Deep Learning Model Acceleration Skydio is seeking a Deep Learning Model Acceleration Engineer to build and scale infrastructure for their AI efforts, focusing on high-performance deep learning inference for computer vision workloads on various hardware platforms. The role involves profiling models, optimizing for low latency and power efficiency, designing MLOps workflows, and implementing GPU kernels for custom architectures. | ServePost-train | 8 |
| Autonomy Engineer - Deep Learning Infrastructure The role focuses on building and scaling the infrastructure for Skydio's Deep Learning (DL) and AI efforts, specifically for computer vision workloads. Responsibilities include developing high-performance inference solutions, optimizing models, designing MLOps workflows, and implementing GPU kernels. The role operates at the intersection of autonomy, embedded, and cloud teams, aiming to accelerate progress in intelligent mobile robots. | ServePost-train | 8 |
| Senior Autonomy Engineer - Deep Learning Senior Autonomy Engineer focused on designing, implementing, and optimizing deep learning models for real-time object detection, tracking, segmentation, and optical flow estimation on embedded drone hardware. The role involves leveraging state-of-the-art methods, curating synthetic and real-world data, and refining models for low-latency performance, with a strong emphasis on software engineering and deploying deep neural networks. | ServeData | 8 |
| Autonomy Engineer - Deep Learning Infrastructure This role focuses on building and scaling the deep learning infrastructure for autonomous flight systems, specifically optimizing inference for computer vision workloads, managing MLOps pipelines, and implementing GPU kernels for custom architectures. It involves working with training or runtime frameworks and model efficiency tools to improve system performance and power efficiency. | ServePost-train | 8 |
| Autonomy Engineer - Deep Learning Model Acceleration The role focuses on building and scaling infrastructure for deep learning and AI efforts, specifically for high-performance inference of computer vision workloads on various hardware platforms. It involves profiling, optimizing, and deploying models, as well as creating MLOps workflows and potentially implementing GPU kernels. The goal is to accelerate progress in intelligent mobile robots by leveraging visual data for semantic and geometric understanding. | ServeData | 8 |