10 months ago
Base Salary
$170k - $237k/yr
Responsibilities
- Develop high-performance, low-latency deep learning inference solutions for computer vision workloads across different hardware platforms.
- Profile computer vision and vision-language models to identify performance bottlenecks, optimization opportunities, and power-efficiency improvements.
- Design and implement end-to-end MLOps workflows for model deployment, monitoring, and retraining.
- Apply machine learning expertise, runtime and training frameworks, and model-efficiency tools to improve system performance.
- Create methods to improve training efficiency.
- Implement GPU kernels for custom architectures and optimized inference.
- Design and implement SDKs enabling customers and external developers to create autonomous ML workflows.
- Uphold and improve Skydio’s engineering standards.
Requirements
- Hands-on experience with MLOps, ML inference optimization, and edge deployment.
- Strong knowledge of deep learning fundamentals, techniques, and modern deep learning architectures.
- Strong fundamentals in computer vision, image processing, and video processing.
- Hands-on experience building and managing ML pipelines for vision or vision-language tasks, including data preparation, training, deployment, and monitoring.
- Experience understanding and addressing security and compliance requirements in ML infrastructure.
- Experience with ML frameworks and libraries.
- Ability to drive concepts through architecture, development, testing, deployment, and monitoring.
- Comfort working within a complex codebase.
- Strong communication and collaboration skills across varying levels of technical depth.
Benefits
- Competitive equity in the form of stock options
- Comprehensive health insurance plans
- Paid vacation time, sick leave, and holiday pay
- 401K savings plan
- Relocation assistance may be provided for eligible roles
Categories
About Skydio
Skydio builds autonomous drones, docking systems, and fleet management software for enterprise, public safety, and defense customers. It sells hardware with AI-based autonomy plus SaaS for fleet operations, inspections, and Drone-as-First-Responder programs. Founded in 2014 and headquartered in San Mateo, California, the company designs and assembles its products in the U.S., with manufacturing in Hayward, and its systems are used across utilities, law enforcement, and the U.S. military.