Backend SDE II (5-8 Years, 80L)

This role is for one of our partner companies, which is a data-centric artificial intelligence infrastructure company that provides data labeling, annotation, and model evaluation services to train and improve machine learning and generative AI models
About the role
We’re looking for a high-agency engineer to build backend systems that ingest, process, and prepare petabyte-scale enterprise data.
You’ll work closely with engineering and research teams to build distributed data platforms, ingestion pipelines, reinforcement learning environments, evaluation harnesses, and research infrastructure. This role is ideal for someone with strong systems judgment who thrives in zero-to-one environments and learns unfamiliar domains quickly.
What you'll own
Design and build distributed backend services that process petabyte-scale enterprise data.
Develop pipelines to ingest, scrub, structure, and store data for downstream research.
Turn recurring project requirements into reliable, reusable platforms for partner labs.
Build RL environments, evaluation tooling, or agentic systems based on your experience and team fit.
Establish technical foundations and engineering processes where no mature playbook exists.
Ship quickly while maintaining high standards for correctness, privacy, reliability, and edge-case handling.
Own systems end to end—from architecture and implementation to deployment and production outcomes.
What we're looking for
Experience designing and operating distributed backend systems in production.
Hands-on experience with large-scale data ingestion, processing, storage, or reliability.
Strong understanding of backend behavior, failure modes, and platform architecture beyond standard ETL workflows.
A track record of building systems from the ground up and making sound technical tradeoffs with incomplete information.
Ability to learn new technical or research domains quickly and translate them into working software.
Broad ownership experience as a founder, founding engineer, technical lead, or end-to-end system owner.
Exposure to AI agents, RL environments, or evaluation harnesses is valuable, but not required.

Skills
Machine Learning, Artificial Intelligence, ETL, Generative AI

Experience
5-8 yrs

Work arrangement
No