Summary
What you’ll impact
The Principal Machine Learning Engineer will lead the data‑science function that curates, validates, and enriches the organization’s petabyte‑scale visual content library using computer vision and AI. Reporting to the CTO, the role combines deep CV algorithm expertise with big‑data engineering to build standards, deploy models, and grow a high‑performing ML team in San Francisco.
Responsibilities
What you'll do
- Multimodal Curation & QC: Manage curation and quality control for one of the market's largest content collections, ensuring library integrity at petabyte scale.
- Automated Enrichment: Deploy CV and LLM models for classification, object detection, and metadata enrichment to enhance content discoverability and value.
- Standards & Criteria Design: Define and automate grading standards tailored to various content types, building consistent and scalable evaluation models.
- Big Data Infrastructure: Execute complex algorithms across AWS and on-site lakehouse environments, focusing on video understanding and multi-modal classifiers.
- Team Building & Mentorship: Recruit, train, and supervise a growing ML team, fostering professional development and maximizing productivity through performance data.
- Strategic Alignment: Partner with Research, Product, and Engineering teams to refine Trust & Safety strategies and ensure the success of project SLAs.
- Executive Reporting: Report directly to the CTO, providing effective communication on risks, mitigation, and the evaluation of scalable tools and processes.
Requirements
What you’ll bring
- 6+ years of experience in ML/Data Science with a core specialty in computer vision (6+ years in machine learning/data science, with computer vision (classification, object detection, content enrichment) as a core specialty.
- Proven track record of operating on large-scale data, demonstrating fluency in both AI algorithm depth and big-data engineering.
- The rare hybrid of CV/AI algorithm depth and big-data engineering ability.
- Experience in leading and mentoring data science teams within a fast-paced environment.
- Video/multimedia expertise and a background in content marketplaces or moderation platforms are significant advantages.