Autonomy Engineer - Deep Learning Model Acceleration at Skydio

Zurich, Zurich, Switzerland -

Full Time

Start Date

Immediate

Expiry Date

18 Feb, 26

Salary

0.0

Posted On

20 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Deep Learning, Computer Vision, MLOps, Model Optimization, Image Processing, Video Processing, Machine Learning, GPU Kernels, SDK Development, Performance Analysis, Data Preparation, Model Training, Model Deployment, Monitoring, Collaboration, Communication

Industry

Aviation and Aerospace Component Manufacturing

Description

Skydio is the leading US drone company and the world leader in autonomous flight, the key technology for the future of drones and aerial mobility. The Skydio team combines deep expertise in artificial intelligence, best-in-class hardware and software product development, operational excellence, and customer obsession to empower a broader, more diverse audience of drone users. From utility inspectors to first responders, soldiers in battlefield scenarios and beyond. About the role: Learning a semantic and geometric understanding of the world from visual data is the core of our autonomy system. We are pushing the boundaries of what is possible with real-time deep networks to accelerate progress in intelligent mobile robots. If you are excited about leveraging massive amounts of structured video data to solve problems in Computer Vision (CV) such as object detection and tracking, optical flow estimation and segmentation, we would love to hear from you. As a deep learning model acceleration engineer, you will be responsible for building and scaling the infrastructure that supports Skydio’s Deep Learning (DL) and AI efforts. You will be working at the nexus of Skydio’s autonomy, embedded and cloud teams to deliver new capabilities and empower the deep learning team. 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 You have demonstrated ability to take a concept and systematically drive it through the software lifecycle: architecture, development, testing, and deployment, and monitoring You are comfortable navigating and delivering within a complex codebase Strong communication skills and the ability to collaborate effectively at all levels of technical depth Compensation: At Skydio, our compensation packages for regular, full-time employees include competitive base salaries, equity in the form of stock options, and comprehensive benefits packages. Compensation will vary based on factors, including skill level, proficiencies, transferable knowledge, and experience. Relocation assistance may also be provided for eligible roles. Fundamentally, we believe that equity is the key to long-term financial growth, and we ensure all regular, full-time employees have the opportunity to significantly benefit from the company's success. Regular, full-time employees are eligible to enroll in the Company’s group health insurance plans. Regular, full-time employees are eligible to receive the following benefits: Paid vacation time, sick leave, holiday pay and retirement savings plan. This position and all associated benefits are subject to applicable federal, state, and local laws, as well as the Company’s policies and eligibility criteria. *For some positions the pay may be dependent upon the individual's regional location. #LI-PG At Skydio we believe that diversity drives innovation. We have created a multidisciplinary environment that embraces the power of diverse perspectives to create elegant solutions for complex problems. We are committed to growing our network of people, programs, and resources to nurture an inclusive culture. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or other characteristics protected by federal, state or local anti-discrimination laws. For positions located in the United States of America, Skydio, Inc. uses E-Verify to confirm employment eligibility. To learn more about E-Verify, including your rights and responsibilities, please visit https://www.e-verify.gov/

Responsibilities

As a deep learning model acceleration engineer, you will build and scale the infrastructure that supports Skydio’s Deep Learning and AI efforts. You will develop solutions for high-performance deep learning inference for computer vision workloads.