Applied Research Engineer

About Us Sieve is a multi-modal lab curating the world's highest-quality training datasets — spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure and novel multimodal understanding techniques that push the frontier of foundation models. Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data. We partner with top AI labs and did $XXM last quarter alone, as a team of ~30 people. We also raised our Series A from Tier 1 firms such as Matrix Partners, Swift Ventures, Y Combinator, and AI Grant. Why Now Sieve is one of the most capital-efficient teams in AI — roughly 30 people serving the world's leading AI labs across every major data modality. You'll join early, own problems end-to-end, and watch your work ship directly into the models defining the frontier. About the Role As an applied research engineer at Sieve, you’ll build high performance building blocks and large scale pipelines to understand video with high precision at internet scale. Often this involves working on ambiguous research problems and finding clever techniques to solve them. You will be working in the computer vision, audio processing, and text processing domains. You’re likely a good fit if you’re comfortable working with models + APIs and squeezing every drop of performance out of them through clever pre/post-processing, parallelism, pipelining, inference optimization, and occasionally fine-tuning. Requirements 2+ years of experience in computer vision or audio processing Strong Python developer with hands-on experience in PyTorch or similar ML frameworks Excellent communication skills, especially with customers and external teams Writes clean, maintainable code — bonus points for active GitHub or portfolio projects Deep passion for the video domain and media technologies Motivated by building end-to-end products—not just training models Able to break problems down from customer level impact to necessary building blocks. Bonus: Active contributor to open source projects Bonus: Experience as an early hire at a startup Benefits 401k + Full Health Insurance Breakfast, Lunch, and Dinner covered and your choice of snacks Ubers covered home *all roles at Sieve require you to be onsite in San Francisco 5 days per week #J-18808-Ljbffr Sieve, Inc.