Description:

RYZ Labs is seeking an experienced Machine Learning Infrastructure Engineer to join their client's team.
The ML platform is essential for training and testing various ML models and analyzing large amounts of sensor data.
The role involves building and enhancing the ML infrastructure, including ETL pipelines, continuous training pipelines, and an annotation platform.
Responsibilities include developing an MLOps system for managing ML training and inference pipelines, improving ML model development processes, and collaborating with ML engineers to design metrics for ML tasks.
The engineer will implement algorithms for ranking annotation candidates and work with annotation providers on quality control and feedback loops.
The goal is to make sensor data widely 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 3+ years of industry experience in building and improving large-volume ML training and validation pipelines.
Experience in building native cloud applications and large-scale data processing pipelines in production is necessary.
Proficiency in at least one programming language such as C++, Python, or Go is required.
Hands-on experience and knowledge of Computer Vision and Deep Learning are essential.
A strong tendency to automate workflows is expected.

RYZ Labs offers a remote work environment with teams distributed throughout the US and Latam.
Employees will have the opportunity to work with cutting-edge technologies in cloud computing.
The company promotes autonomy and efficiency, allowing employees to own their development processes.
There are opportunities for learning, growth, and working on challenging projects.
RYZ Labs values a customer-first mentality, urgency, ownership, humility, respect, frugality, and continuous improvement.