Description:

Serve Robotics is seeking a Software Infrastructure Engineer for their Machine Learning Operations (ML Ops) team to enhance their ML platform.
The role involves developing and maintaining ML infrastructure, including sensor data ETL pipelines, continuous training pipelines, and an annotation platform.
The engineer will 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 position requires designing and implementing algorithms for ranking and scoring annotation candidates.
The engineer will also work with annotation providers to establish quality control and feedback loops.
Making sensor data and its derivatives accessible for Robotics Engineers across the company is a key responsibility.

Requirements:

A Bachelor’s degree in computer science with a focus on data engineering and large-scale ML systems is required.
Candidates must have at least 3 years of industry experience in building, running, and improving large-volume ML training and validation pipelines.
Experience in building native cloud applications is necessary.
Proven experience in developing large-scale data processing pipelines in production is required.
Proficiency in at least one programming language such as C++, Python, or Go is essential.
Hands-on experience and a solid understanding of Computer Vision and Deep Learning are required.
A strong inclination to automate workflows for oneself and others is necessary.

Serve Robotics offers a full-time employment opportunity with a focus on innovative technology in robotics and machine learning.
Employees will be part of a diverse and agile team dedicated to solving real-world problems.
The company provides an environment that encourages collaboration and respect among team members.
Opportunities for professional growth and development in cutting-edge technology fields are available.