Tech Stack

Description

You will design and build foundational systems for MLOps and deep learning infrastructure, enabling robots with advanced machine learning capabilities. You'll develop scalable infrastructure for training and deploying models, optimize compute resources, and build tools for model understanding and analysis.

Requirements

• Bachelor's degree in Computer Science, Robotics, Machine Learning, or related technical field.
• 2 years of experience in software development with focus on MLOps or ML infrastructure.
• Proficiency in Python and C++.
• Experience with Docker and Kubernetes.
• Experience with deep learning frameworks (TensorFlow, JAX, or PyTorch) and cloud computing (Google Cloud Platform).

Responsibilities

• Design and implement scalable infrastructure for training and deploying deep learning models on a real-time robotic control stack.
• Optimize data loading and training speed across 1000+ GPU training jobs.
• Build data pipelines supporting distributed computing for processing large volumes of robotics data.
• Develop APIs and tools for internal and external researchers to integrate machine learning techniques.
• Optimize allocation of compute resources (GPUs, TPUs) and create orchestration workflows on GKE.