Autonomy Engineer - Deep Learning Model Acceleration

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.

Key responsibilities

• Develop high‑performance deep learning inference solutions for computer‑vision workloads across multiple hardware platforms.
• Profile CV and Vision Language Models to identify bottlenecks, improve power efficiency and optimize throughput.
• Design and implement end‑to‑end MLOps workflows for model deployment, monitoring and re‑training.
• Create GPU kernels for custom architectures and optimized inference.
• Build SDKs that enable customers and external developers to create autonomous workflows using machine learning.

Required profile

• Hands‑on experience with MLOps, ML inference acceleration/optimization, and edge deployment.
• Strong knowledge of deep‑learning fundamentals, state‑of‑the‑art models and architectures.
• Solid background in computer vision, image and video processing.
• Experience building and managing ML pipelines for vision or vision‑language tasks, including data preparation, training, deployment and monitoring.
• Understanding of security and compliance requirements in ML infrastructure.
• Proficiency with ML frameworks and libraries.

Required skills

• MLOps
• ML inference acceleration
• Edge deployment
• Deep learning fundamentals
• Computer vision
• GPU kernel development
• SDK development
• Security and compliance in ML