Rethink recruit
At Sieve, we're reimagining how machines understand video. We're a fast-growing team building cutting-edge AI systems that extract meaning from dynamic, real-world content-automatically, scalably, and in real time.
We're looking for a Applied Research Engineer who thrives in fast-paced, high-ownership environments and wants to push the boundaries of multimodal AI. You'll work with some of the latest Visual Language Models (VLMs) and generative models to build systems for a wide range of video understanding, editing, and search applications. This often means tackling ambiguous research problems and using creative approaches to solve them.
What You'll Do
- Design, train, and deploy deep learning models to extract insights from video at scale
- Build robust, performant pipelines in Python for real-time and batch processing
- Squeeze every drop of performance from models through clever pre/post-processing, pipelining, inference optimization, and fine-tuning
- Collaborate closely with product and customers to turn ambiguous problems into working systems
- Prototype with VLMs and multi-modal architectures to push Sieve's technology forward
- 4+ years experience in ML engineering, ideally in a startup or similarly scrappy, fast-moving environment
- Strong background in deep learning (PyTorch/TensorFlow) and computer vision
- Fluency in Python and best practices for scalable ML code
- Experience building AI systems to solve real customer problems
- A portfolio of side projects, demos, or contributions (GitHub, HuggingFace, etc.)
- Bonus: research background in ML, experience with CUDA, or open-source contributions
At Sieve, we care deeply about ownership, speed, and craft . If you're someone who loves building impactful ML systems, iterating quickly, and solving novel problems with creativity and rigor-you'll feel right at home.