AI Safety Engineer: Build Safety Data Pipelines

Trajectory Labs; Berkeley (CA); Hybride; USD 250 000 - 400 000; Plein temps

Avantages offerts par ce poste

Health coverage

401(k)

Food: Catered meals and snacks

Relocation allowance

Résumé du poste

Trajectory Labs seeks a Member of Technical Staff to build a software factory that produces safety data for training and evaluating AI models. You will work with technical leads to develop training-data pipelines, environments, and evaluations that improve model safety.

This role is at an early-stage startup where responsibilities grow quickly. You will own engineering tasks, write production code, test, and debug while collaborating with leads on customer relationships and architecture

Qualifications

• Impact-driven: you want to improve the safety of frontier AI systems.
• Agent-native engineering: you use coding agents and LLMs as core development tools.
• Strong software engineering: you can design, build, test, and debug substantial systems, including code produced by agents.
• Autonomy and judgment: you can break down an engineering task, make good trade-offs, and keep the work moving.

Responsabilités

• Build evaluations, RL environments, and training-data pipelines.
• Write production code, develop tests, debug failures and improve reliability.
• Develop reusable tools and infrastructure for faster, trustworthy projects.
• Collaborate with engineers and researchers on larger technical problems.

Connaissances

Impact-driven

Agent-native engineering

Strong software engineering

Autonomy and judgment

Early-stage startup drive

Description du poste

Trajectory Labs seeks a Member of Technical Staff to build a software factory that produces safety data for training and evaluating AI models. You will work with technical leads to develop training-data pipelines, environments, and evaluations that improve model safety.

This role is at an early-stage startup where responsibilities grow quickly. You will own engineering tasks, write production code, test, and debug while collaborating with leads on customer relationships and architecture