Description:

Serve Robotics is seeking a Software Engineer for their Machine Learning Infrastructure team to enhance their ML platform, which is crucial for the autonomy of their sidewalk robots.
The role involves developing and maintaining ML infrastructure, including sensor data ETL pipelines, continuous training pipelines, and an annotation platform.
The engineer will also develop an MLOps system to manage the lifecycle of ML cloud training and inference as a service pipelines, and improve ML model development and deployment processes.
Collaboration with ML engineers to design metrics for ML tasks and mining sensor data is essential.
The engineer will design and implement algorithms for ranking and scoring annotation candidates and work with annotation providers to establish quality control and feedback loops.
The goal is to make sensor data and its derivatives accessible for Robotics Engineers across the company.

Requirements:

A BS or MS in computer science with a focus on data engineering and large-scale ML systems is required.
Candidates must have at least 2 years of industry experience in building, running, and improving large-volume ML training and validation pipelines.
Experience in building native cloud applications is necessary.
Proficiency in large-scale data processing pipelines in production is required.
Candidates should be proficient in at least one programming language: C++, Python, or Go.
Hands-on experience and a solid understanding of Computer Vision and Deep Learning are essential.
A strong tendency to automate workflows for oneself and others is expected.

Serve Robotics offers a full-time employment opportunity with the chance to work remotely from anywhere in the USA.
Employees will be part of a diverse and agile team of tech industry veterans dedicated to solving real-world problems through robotics and machine learning.
The position provides an opportunity to contribute to innovative projects that aim to transform urban delivery systems.
Employees will have access to cutting-edge technologies and the chance to work collaboratively in a respectful environment.