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About the Role
Chakra Labs is building high-fidelity environments, evaluations, and datasets for frontier AI research. We work with top AI labs to encode human taste into intelligence, focusing on measurable, useful, and hard-to-fake improvements in AI models.
Responsibilities
- Develop new environment modalities, evaluation tasks, and datasets for frontier AI research.
- Transform researcher hunches into shipped deliverables, pushing the boundaries of agent capabilities.
- Create high-fidelity environments, task distributions with grading logic, and datasets to demanding specifications.
- Write environment code, task specifications, and scoring harnesses.
- Identify and generalize custom builds into the core product to compound capabilities.
Requirements
- Strong generalist engineering skills across backend services, data pipelines, and frontend development.
- Ability to turn loosely-defined research questions into concrete, validated deliverables.
- Clear communication with researchers and technical customers, including pushing back on incorrect requests.
- Comfort working in both deep async stretches and high-bandwidth sessions.
- Genuine interest in how AI agents fail and how to measure it.
- Ability to learn task design, LLM-judged scoring, and reward hacking detection on the job.
- Ideally at least 3 years of experience shipping production software, though less is acceptable if other qualifications are met.
Skills
- TypeScript/Python
- Full-stack development
- Backend services
- Data pipelines
- Frontend development
- Task design
- LLM-judged scoring
- Reward hacking detection
Location
- Remote
Work Type
- Full-time
Experience Level
- Mid-level
- Senior
Benefits
- Opportunity to work with cutting-edge technologies across the data, AI, and infrastructure stack.
- Ownership of whole deliverables and customer relationships.
- Work with a small, experienced team with a track record of shipping high-impact products.
About the Company
- Chakra Labs' mission is to encode human taste into intelligence.
- We build high-fidelity environments, evals, and datasets for frontier AI research.
- Our work focuses on the frontier of post-training, agent environments, data quality, and research infrastructure.
- We aim to build systems that measurably improve AI models in ways that are useful and hard to fake.