Bachelor's degree or equivalent practical experience.
5 years of Python coding experience.
3 years developing large-scale infrastructure or distributed systems.
3 years working with Generative AI agents.
2 years of multithreading experience.
Responsibilities
Design, build, and maintain reusable evaluation infrastructure blocks.
Enhance scalability, reliability, and efficiency of large-scale evaluation workflows.
Onboard product teams and resolve their issues, creating self-serve features.
Implement secure data isolation and access control for evaluation data.
Facilitate transition from offline evaluations to live experiments and production.
Benefits
15% bonus target
Equity benefits
Comprehensive health coverage
Flexible work arrangements
Professional development opportunities
Full Job Description
info_outline X In most instances, this position requires in-person interviews as part of the hiring process.
Minimum qualifications:
Bachelor's degree or equivalent practical experience.
5 years of experience with coding in Python.
3 years of experience developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
3 years of experience working with Generative AI agents.
2 years of experience with multithreading.
Preferred qualifications:
Master's degree or PhD in Computer Science or a related technical field.
2 years of experience with large-scale data processing, storage systems, or workflow orchestration.
2 years of experience working with two or more of the following: distributed and parallel systems, machine learning, information retrieval, natural language processing, Unix/Linux environments, or security and access control.
Experience with ML infrastructure, model evaluation, or LLM and GenAI workflows (e.g., autoraters, metrics, or experimentation platforms).
Experience developing in Python and C .
About the job
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Design, build, and maintain reusable eval infra blocks, such as streaming evaluation, autorater pipelines, and metric aggregation.
Make large-scale eval workflows more scalable, reliable, and efficient across compute, storage, and serving backends.
Onboard product teams, debug their issues, and turn recurring needs into self-serve features.
Build secure per-customer data isolation and access control for eval data and results.
Help teams move smoothly from offline evals to online evals and to live experiments and production.
About Google
Google is a multinational technology company that specializes in Internet-related services and products. These include online advertising technologies, search engine, cloud computing, software, and hardware. Google was founded in 1998 by Larry Page and Sergey Brin while they were Ph.D. students at Stanford University. The company has grown tremendously since then and has become one of the most valuable companies in the world. Google's mission is to organize the world's information and make it universally accessible and useful.
