Autonomy Engineer - Deep Learning Infrastructure

Skydio; San Mateo (CA); On-site; USD 170,000 - 236,500; Full time

Benefits offered by this job

Stock options

Comprehensive health insurance

Paid vacation and sick leave

401K savings plan

Job summary

A leading drone technology company in California seeks a Deep Learning Infrastructure Engineer to build and scale infrastructure for their AI initiatives. The role requires hands-on experience with MLOps and optimization techniques to enhance model performance. You will work cross-functionally to develop end-to-end solutions for high-performance deep learning and contribute to advancing the company's autonomous systems. Competitive compensation ranging from $170,000 to $236,500, with comprehensive benefits are offered.

Qualifications

• Hands-on experience with MLOps and edge deployment.
• Strong knowledge of deep learning fundamentals and models.
• Experience building ML pipelines for vision tasks.

Responsibilities

• Develop solutions for high-performance deep learning inference.
• Profile models to analyze performance and optimize efficiency.
• Design and implement MLOps workflows for model handling.

Skills

MLOps

Deep Learning Inference Optimization

Computer Vision

Machine Learning Pipelines

Tools

TensorFlow

PyTorch

scikit-learn

Job 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.

Skydio is the leading US drone company and the world leader in autonomous flight. We leverage breakthrough AI to create the world's most intelligent flying machines for use by enterprise and government. 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.

About the role

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.

How you'll make an impact

As a deep learning infrastructure engineer, you will be responsible for building and scaling the infrastructure that supports Skydio’s 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.

• 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
• 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. The annual base salary range for this position is $170,000 - 236,500*. 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 401K 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.

* Compensation for certain positions may vary based on the position’s location.

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/