Sieve

Build strategic relationships and demand-generation programs across frontier AI labs, model companies, and the AI data ecosystem. The role requires deep AI ecosystem familiarity, technical understanding of foundation-model data needs, and exceptional relationship-building skills.

The Growth Associate will source, recruit, and activate US-based domain experts while building partnerships with specialized firms. The role requires 2–4 years of recruiting or B2B sales experience, strong English communication, and availability for evening India Standard Time hours.

Machine Learning Engineer owning the full ML lifecycle for multimodal video datasets at Sieve. Fine-tune VLMs, build evaluation/QA pipelines with frontier models, design filtering systems over internet-scale data, and ship production improvements for top AI labs. Requires strong Python, PyTorch, and production ML experience.

Deployed Research Engineer works directly with AI labs to build custom algorithms, models, and pipelines for high-quality video datasets at scale. Requires strong Python/PyTorch skills, customer collaboration, and end-to-end delivery from prototypes to production.

Owns execution and scaling of data operations platform, managing workforce, QA processes, partnerships growth, and product ops initiatives. Requires mixed technical skills, organizational strength, growth mindset, and bachelor's in CS/STEM.

Designs and maintains reliable infrastructure for petabyte-scale video processing across multi-cloud environments. Owns incident response, observability (Prometheus, OpenTelemetry), security, and CI/CD tooling with 3+ years experience in scalable systems.

Builds and scales a full-stack video collection platform with mobile features for user submissions, internal tools, and high-reliability systems. Requires strong TypeScript/React frontend, React Native mobile, Python/Go backend experience, and high ownership in a fast-paced startup.

Leads relationships with top AI lab customers, serving as technical contact to manage accounts, drive revenue expansion, and translate needs into engineering priorities. Requires deep ML/AI knowledge, strong networks in AI labs, and customer-facing technical experience.

Builds and scales data pipelines for video AI datasets, owning end-to-end projects from sourcing to delivery with ML filters and dashboards. Requires strong Python skills, clean code practices, and customer communication.

Designs and engineers distributed systems for compute, scheduling, and orchestration of ML and ETL pipelines handling large-scale video data. Requires 3+ years building data infrastructure, proficiency in Go/Python, and experience with petabyte-scale pipelines and CI/CD.