Data Annotation Specialist - Software Engineer (OpenClaw Trajectory Evaluation)

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

Offer Details

• Engagement type: Contractor assignment/freelancer (no medical/paid leave)
• Duration: 5 weeks

Evaluation Process

• Resume screening
• Take home assessment (60 mins)