about 3 hours ago
Base Salary
$150k - $350k/yr
Responsibilities
- Own model quality for customer-facing video understanding problems.
- Fine-tune vision-language and multimodal foundation models for specialized tasks.
- Build automated evaluation and QA pipelines using frontier models.
- Design high-precision filtering, ranking, retrieval, and labeling systems over internet-scale video datasets.
- Create datasets, benchmarks, and evaluation frameworks that continuously improve model quality.
- Develop production ML pipelines spanning preprocessing, inference, post-processing, and quality validation.
- Work directly with frontier AI labs to translate ambiguous requirements into scalable ML systems.
- Ship improvements quickly, measure results, and iterate based on real-world performance.
Requirements
- Strong Python engineer with experience building production ML systems.
- Experience training, fine-tuning, or deploying modern deep learning models.
- Comfortable working with PyTorch and modern foundation models.
- Excellent intuition for evaluation, dataset quality, precision/recall tradeoffs, and edge cases.
- Enjoys rapidly prototyping with new AI models and APIs.
- Comfortable owning projects from customer problem to internal pipelines to deployed solution.
- Strong communicator who enjoys working directly with customers and cross-functional teams.
- Excited by video, multimodal AI, and frontier foundation models.
- In-person at our SF HQ.