Company brief · updated 2026-10-19
sievedata.com · B2B · High-quality video, audio, image, and interaction data for frontier AI.
Today: Capturing multimodal data across real-world, digital and simulated environments
Roles: International Field Operations Lead · Strategic Partnerships & Ops Lead, Physical AI
Requirements mention: on-the-ground operations · hire and manage people · footage recording · Language skills · physical AI · human-in-the-loop data operations
Inference: Sieve is expanding its own real-world capture. The postings describe field teams abroad that record footage, and partnerships that open factories and manufacturing lines for Physical AI training data. Both roles opened 2026-10-05 in San Francisco.
Today: Dense labels, annotations and human QA at scale
Roles: Product Operations Lead · Strategic Partnerships & Ops Lead, Physical AI
Requirements mention: human-in-the-loop data operations · workforce management · task assignment · QA processes · annotation pipelines · data ops platform
Inference: Sieve is building out the workforce, task assignment and QA tooling behind its labeling work. Both roles list the same data-operations requirements.
Today: Sourcing video and human data from contributors
Roles: Member of Technical Staff, Product · Growth Associate · Product Operations Lead
Requirements mention: video collection platform · media capture · upload flows · expert network recruiting · US-facing recruiting · user acquisition · sourcing campaigns
Inference: Sieve is growing the supply side of its data, meaning paid video contributors (the posting describes a platform that pays contributors for recordings) and a US-facing expert network recruited through outbound.
Today: Filtering, indexing and packaging video and multimodal datasets
Roles: Member of Technical Staff, Forward Deployed · Member of Technical Staff · Member of Technical Staff, Machine Learning
Requirements mention: exabyte-scale data infrastructure · large-scale data pipelines · dataset quality · production ML pipelines · filtering, ranking, retrieval, and labeling systems
Inference: Sieve is adding engineering capacity for the systems that filter, label and evaluate video datasets at scale. The three Engineering roles opened 2025-09-02, 2026-05-14 and 2026-07-13.
Today: Training data for frontier video and audio-visual AI
Roles: Member of Technical Staff, Applied Research
Requirements mention: post-training · supervised fine-tuning · preference optimization · reproducible training and evaluation pipelines
No inference: a single role opened 2026-09-14. The posting says it trains and evaluates multimodal models to understand how data shapes their capabilities in video generation and audiovisual understanding.
Today: Custom datasets for AI research teams
Roles: Business Development · Research & Product Lead
Requirements mention: strategic business development · partnerships · human data · RL environments · technical scoping · proposal development · demos · customer data pipelines
Inference: Sieve is staffing the customer-facing work of scoping and selling custom data to teams building foundation models, including human data, RL environments and evaluations.
| Department | Open |
|---|---|
| Engineering | 7 |
| Business Operations | 4 |
| Product | 4 |
| GTM | 1 |
13 open roles: Engineering 5, Product 4, Business Operations 3, GTM 1. The Product roles are mostly data-operations jobs (field capture, workforce, QA) rather than software, so the hiring leans toward running data collection as much as building pipelines. 11 roles are in San Francisco; 3 opened and 2 closed in the last 30 days.
Seniority: 5 senior, 4 mid, 1 junior, 3 unknown.
Skills named most: Python, PyTorch, exabyte-scale data infrastructure, ML data pipelines, data tooling, QA workflows, human-in-the-loop data operations, Go, post-training, Sales Navigator, Apollo, Clay
Locations: San Francisco (11 roles, not remote); Anywhere (1 role, remote, Business Operations); India (1 role, remote, Business Operations).
If you're applying: If you work in data operations, look at the Product roles; if you build data pipelines or ML systems, look at the Engineering roles. Check the fit lines first: 11 of 13 roles are in San Francisco and not remote, and only the Operations Associate (Anywhere) and the Growth Associate (India) are remote.
If you're selling or recruiting: Sieve is staffing field and industrial data capture, labeling workforce and QA, contributor and expert sourcing, and dataset pipeline engineering. Vendors of annotation workforce, field logistics, recruiting and outbound tooling, or large-scale data infrastructure have the clearest fit. The Business Development and Research & Product Lead roles show customer-facing work with foundation model teams.
| Title | Department | Location | Posted |
|---|---|---|---|
| Member of Technical Staff, Robotics Research | Engineering | San Francisco | 2026-10-23 |
| Roboticist, Physical AI | Engineering | San Francisco | 2026-10-23 |
| Country Launch Ops Lead | Business Operations | Shenzhen | 2026-10-19 |
| Operations Associate | Business Operations | Anywhere (remote) | 2026-10-15 |
| International Field Operations Lead | Product | San Francisco | 2026-10-05 |
| Strategic Partnerships & Ops Lead, Physical AI | Product | San Francisco | 2026-10-05 |
| Member of Technical Staff, Applied Research | Engineering | San Francisco | 2026-09-14 |
| Business Operations | Business Operations | San Francisco | 2026-09-14 |
| Business Development | GTM | San Francisco | 2026-09-01 |
| Growth Associate | Business Operations | India (remote) | 2026-07-28 |
| Member of Technical Staff, Machine Learning | Engineering | San Francisco | 2026-07-13 |
| Member of Technical Staff, Forward Deployed | Engineering | San Francisco | 2026-05-14 |
| Product Operations Lead | Product | San Francisco | 2026-03-11 |
| Member of Technical Staff, Product | Engineering | San Francisco | 2026-01-27 |
| Research & Product Lead | Product | San Francisco | 2025-09-24 |
| Member of Technical Staff | Engineering | San Francisco | 2025-09-02 |