Key Responsibilities

Data Curation & Labeling Operations
Manage end-to-end data labeling workflows
Enqueue datasets for labeling and maintain labeling interfaces
Extract structured labels for modeling teams
Manually annotate training data when required
Audit and correct human-labeled data


Data Engineering & Pipelines

Maintain and optimize large-scale data processing pipelines (billions of images)
Support data sourcing and content understanding using ML models
Leverage LLMs to clean, annotate, and evaluate data
Assist in building efficient ETL workflows


Data Governance

Maintain dataset portfolio with proper access controls
Ensure compliance with data retention and privacy standards
Support governance and documentation practices


Analysis & Model Evaluation

Identify model quality gaps using structured evaluation protocols
Collaborate with engineers to summarize findings and recommend improvements
Mine and prepare new datasets for iterative model training
Scale validated evaluation frameworks across product teams


Required Qualifications

Associate’s degree or equivalent training in Computer Science, Engineering, Physics, Bioinformatics, or other STEM field
Basic knowledge of Python and SQL
Foundational understanding of computer vision and generative AI models
Experience with data ETL workflows or pipelines
Familiarity using LLMs for data labeling or evaluation tasks
Strong attention to detail and analytical thinking


Preferred Qualifications

Prior industry experience in software development, QA, or research
Exposure to human-computer interaction or ML evaluation work
Experience working in large-scale technology environments
Strong written and verbal communication skills


Work Environment

Onsite collaboration with engineering teams in Menlo Park, CA
Fast-paced, research-driven environment
High-impact role supporting next-generation AI systems

Salary : N/A

Company : North Star Staffing AU

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