Senior Software Engineer, ML Infrastructure
July 25
🏡 Remote – Anywhere in California
Description
• Develop and maintain ML infrastructure, such as sensor data ETL pipelines, hard example data mining, continuous training pipelines, annotation platform, etc. • Develop MLOps system for managing lifecycle of ML cloud training and inference as a service pipelines. Continuously improve ML model development, management and deployment processes. • Work together with ML engineers, design metrics for ML tasks to mine sensor data of interest. • Design and implement algorithms, such as collaborative filtering, active learning, etc., to rank/score annotation candidates. • Work with annotation provider on setting up the annotation process, quality control and feedback loops. • Make sensor data and its derivatives widely discoverable and accessible for Robotics Engineers across the entire company.
Requirements
• BS or MS in computer science with focus in data engineering and large scale ML systems • 3+ years of industry experience building, running and improving large-volume ML training and validation pipelines. • Experience with building native cloud applications • Experience with large scale data processing pipelines in production. • Proficient in at least one of the following languages: C++, Python, or Go. • Hands-on experience and good knowledge of Computer Vision and Deep Learning. • Strong tendency to automate own and others’ workflows.
Apply Now
