About the RoleAs a Forward Deployed Engineer at Sieve, you'll work on highly specific dataset problems for frontier AI labs and build the custom algorithms, models, and pipelines needed to solve them.
We're looking for someone with a strong bias to action who likes working closely with customers, untangling messy requirements, and shipping fast. You'll work closely with customers and internal teams to understand exactly what data is needed, then turn ambiguous requirements into production systems that can find, generate, filter, transform, evaluate, and package high-quality video datasets at scale.
The work often spans computer vision, audio processing, text processing, metadata analysis, model adaptation, and quality evaluation. You should be comfortable moving between research prototypes and reliable production pipelines, using models and APIs creatively, and squeezing performance through pre/post-processing, parallelism, inference optimization, fine-tuning, and evaluation loops.
Requirements- Comfortable working directly with customers or external teams to translate ambiguous needs into concrete technical systems
- Strong Python developer with hands-on experience in PyTorch or similar ML frameworks
- Experience building custom algorithms, model workflows, or large-scale data pipelines
- Strong intuition for dataset quality, filtering, labeling, evaluation, and edge cases
- Able to break customer-level goals down into the models, heuristics, infrastructure, and QA steps needed to deliver
- Writes clean, maintainable code and can move quickly without creating brittle systems
- Deep passion for video, media technologies, and frontier AI applications
- Motivated by delivering end-to-end outcomes, not just training models or writing research code
- Bonus: Experience with large-scale video, audio, or multimodal data processing
- Bonus: Active contributor to open source projects
- Bonus: Experience as an early hire at a startup
- In-person at our SF HQ
Benefits- 401k + Full Health Insurance
- Breakfast, Lunch, and Dinner covered and your choice of snacks
- Ubers covered home
