Jr. AI Engineer - Data Annotation
Skills
Analytical SkillsContextDashboardsData ScienceLabelsQuality ProcessesSTEM
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Solid programming ability with hands-on Python experience and comfort with scripts SQL and data wrangling
- Ability to use agentic development tools or ramp up quickly
- Quality-first mindset with strong attention to detail in messy data
- Dependable and adaptable with the ability to context switch as priorities shift
- Energized by real-world data and collaboration with data-minded teammates
- Hungry self-directed and ready to grow in a fast-moving environment
Nice to have
- Recent grad
- CS background
- STEM background
- Critical thinker
- Fast learner
Day to day
- Do hands-on data annotation and quality control by labeling reviewing and correcting classification outputs as part of the data science pipeline
- Improve and scale annotation workflows by identifying bottlenecks repetitive steps and error sources then fixing them with Python SQL and agentic tools
- Build and run QC checks that catch labeling errors measure inter-annotator agreement and surface systematic issues before production
- Work closely with data scientists and ML engineers to connect label quality with model performance and keep processes documented for scaling and onboarding
- Context switch across labeling quality analysis scripting and process work as priorities evolve in a fast-moving environment