TL;DR

Machine Learning Systems Engineer (AI): Developing and optimizing encodings and tokenization systems for Finetuning workflows with an accent on building critical infrastructure that impacts model learning. Focus on collaborating with research teams to enhance data representation and improve training efficiency.

Location: Hybrid (at least 25% in office)

Salary: $320,000 - $405,000

Company

%hirify_global% is a public benefit corporation focused on creating reliable and interpretable AI systems.

What you will do

Design, develop, and maintain tokenization systems for Pretraining and Finetuning workflows.
Optimize encoding techniques to enhance model training efficiency.
Collaborate with research teams to address evolving data representation needs.
Build infrastructure for experimenting with novel tokenization approaches.
Implement monitoring systems for tokenization-related issues.
Create testing frameworks for validating tokenization systems.

Requirements

Bachelor's degree in a related field or equivalent experience.
Significant software engineering experience with machine learning expertise.
Proficiency in Python and familiarity with modern ML practices.
Strong analytical skills to evaluate engineering impacts on research outcomes.
Experience with machine learning data processing pipelines.