Autonomy DL Infra Engineer

Perot Jain; San Mateo, Northern (CA, KY); Hybrid; USD 170,000 - 237,000; Full time

Benefits offered by this job

Equity in stock options

Relocation assistance may be provided

Group health insurance plans

Job summary

Skydio, a leading US drone company, seeks a Deep Learning Infrastructure Engineer in San Mateo to design and scale the infrastructure powering DL/AI efforts. You’ll work across autonomy, embedded, and cloud teams to deliver new capabilities and optimize CV workloads.

You will build end-to-end MLOps, profile and optimize CV/VLM models, and implement high-performance inference across hardware, while upholding Skydio’s engineering standards and security requirements.

Qualifications

• 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.
• 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.
• 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.

Responsibilities

• 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

Skills

MLOps

ML inference optimization

edge deployment

DL fundamentals

CV / Vision processing

Vision-language tasks

software lifecycle

communication skills

Tools

ML frameworks

Job description

Skydio, a leading US drone company, seeks a Deep Learning Infrastructure Engineer in San Mateo to design and scale the infrastructure powering DL/AI efforts. You’ll work across autonomy, embedded, and cloud teams to deliver new capabilities and optimize CV workloads.

You will build end-to-end MLOps, profile and optimize CV/VLM models, and implement high-performance inference across hardware, while upholding Skydio’s engineering standards and security requirements.