Skydio
Autonomy Engineer - Deep Learning Infrastructure
$170K–$236K
San Mateo, California, United States · Hybrid · Full-time · Posted Dec 15, 2025
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About the job
Build and scale deep learning infrastructure for computer vision workloads, including efficient inference, MLOps, training workflows, GPU kernels, and ML-enabled developer SDKs.
What you'll do
- Develop and optimize high-throughput, low-latency deep learning inference across hardware platforms, including profiling models and improving power efficiency.
- Design end-to-end MLOps and training workflows for model deployment, monitoring, and retraining; implement custom GPU kernels.
- Build SDKs that enable customers and external developers to create autonomous workflows using ML.
What they ask for
- Hands-on experience with MLOps, ML inference optimization, and edge deployment.
- Strong knowledge of deep learning fundamentals and models, plus computer vision, image processing, and video processing.
- Hands-on experience building and managing ML pipelines for vision or vision-language tasks, covering data preparation, training, deployment, and monitoring.
- Experience with ML frameworks and libraries, and understanding of security and compliance requirements in ML infrastructure.
Pay
$170,000 - $236,500 USD annual base salary
Tools
GPU
AI focus
Deep learning infrastructure and computer vision AI, including inference optimization, model training and deployment, vision-language models, and ML-powered autonomous workflows.
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