Title: llm data specialist (python, ai annotation, research tasks)
job type: short term contract
role overview
we are looking for highly analytical professionals to join as s3 annotators, responsible for producing and validating advanced openclaw trajectories for research-oriented tasks involving ambiguous goals, multi-step reasoning, and long-context workflows. This role requires strong problem-solving ability, research thinking, and the capability to justify decisions while executing complex, multi-tool workflows used to train sophisticated ai agents.
what does day-to-day look like
create and validate openclaw trajectories for complex, research-oriented tasks
work on tasks such as data analysis, web research, and document synthesis
operate under underspecified or ambiguous goals, making logical and defensible decisions
use python (notebooks, scripts) for data processing, automation, and analysis
perform workflows spanning multiple tools, environments, and applications
clearly document both what actions were taken and why they were taken
review and improve trajectory quality for reasoning depth and correctness
collaborate with teams to refine evaluation standards and annotation frameworks.
requirements
background in research, data science, engineering, or related fields (academic or industry)
5+ years of experience in python / bash, including experience with notebooks and data wrangling
experience with openclaw or similar advanced environments
experience with web research, scraping tools, or data analysis workflows
ability to articulate reasoning behind decisions and steps
experience handling multi-step workflows across tools or platforms
exposure to llm-based tools, ai systems, or agentic workflows
nice to have
academic research experience (thesis, publications, lab work)
familiarity with evaluation methodologies or experimental design
experience in ai evaluation, rlhf, or advanced annotation workflow
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