---
title: 'Data Collection Partnerships Lead at Sieve'
canonical: 'https://feeny.ai/job/data-collection-partnerships-lead-sieve-san-francisco-6m4vwyfgbq4h'
type: 'job'
last_seen: '2026-10-29'
---

# Data Collection Partnerships Lead at Sieve

- **Company:** Sieve
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-10-28
- **Last confirmed live:** 2026-10-29
- **Apply:** https://jobs.ashbyhq.com/sieve/b9d3ebb5-7441-4d38-93b0-1699475af351

## Job description

## About Us

Sieve builds training data that helps AI understand and interact with the world. We work with leading AI labs across video, audio, images, text, and 3D, combining large-scale data infrastructure with multimodal research to improve the data behind frontier models.

## Why Now

Robotics and physical AI need data from people performing real tasks in real environments. Collecting that data at scale requires partners with useful access, capable local teams, and reliable operations. We’re expanding our global network of collection partners. We need someone who can find strong partners, get pilots running quickly, and turn early results into dependable production.

## About the Role

You’ll build and scale Sieve’s network of external data collection vendors, owning both new vendor development and ongoing vendor management. You’ll source and qualify collection companies and local operations teams, negotiate agreements, launch pilots, and manage those relationships through accepted data collection hours and sustained production across countries, environments, and data types. Our partners bring their own access and collection operations. You’ll own those relationships and their commercial and operational performance, working with our hardware, engineering, quality, and delivery teams to ensure the data meets Sieve’s requirements. Strong fits have personally developed external suppliers or operated distributed production networks. You should enjoy both the commercial work of building a partnership and the detailed follow-through that makes it productive.

## What You’ll Do

- Build the vendor pipeline: Own sourcing and qualification of collection vendors across countries, environments, and data types. Assess their access, staffing, equipment, economics, and demonstrated collection capabilities.
- Qualify through real output: Run structured sample reviews and pilots with our technical teams. Establish what a partner can reliably produce before committing to a larger program.
- Own commercial negotiations: Negotiate pricing, payment schedules, volume ramps, and performance commitments. Work with legal and finance to establish clear agreements covering data rights and each party’s responsibilities.
- Turn pilots into production: Translate collection requirements into concrete partner plans, milestones, and onboarding steps. Coordinate internal support so promising partners move into production quickly.
- Own ongoing vendor management: Manage the relationship beyond onboarding and pilots. Run regular reviews of accepted data collection hours, quality, cost, coverage, and delivery reliability. Expand successful vendors and address underperformance directly.
- Resolve operational blockers: Work with partners and internal teams to fix collection, upload, equipment, and quality issues. Set corrective actions, assign owners, and follow through until problems are resolved.
- Build a repeatable operating system: Maintain clear records of agreements, specifications, pilot results, production capacity, and risks. Create playbooks for pricing & region targets, qualifying partners more quickly, and more.

What Success Looks Like

- Promising partners move efficiently from first conversation to successful pilots and sustained production.
- Accepted, usable data grows with predictable quality, cost, and delivery timelines.
- Capacity forecasts reflect demonstrated performance and credible ramp plans.
- Partner issues are resolved without constant intervention from founders or technical leads.
- The network expands across useful tasks, environments, and geographies.

## Requirements

- 5+ years of relevant experience in supplier development, vendor operations, data operations, outsourcing, or a related role with direct responsibility for external partner delivery.
- A track record of personally sourcing, negotiating with, onboarding, and scaling suppliers or operational partners.
- Experience managing partner performance against quality, volume, timeline, and cost commitments—including resolving missed targets and difficult commercial conversations.
- Strong commercial and analytical judgment. You can evaluate pricing, model unit economics, build capacity forecasts, and identify the constraint behind a missed target.
- Technical fluency and curiosity. You can learn collection requirements, turn them into clear partner instructions, and work effectively with engineering and quality teams.
- Disciplined organization, clear communication, and consistent follow-through across multiple partners, countries, and time zones.
- Willingness to travel to partner operations when needed. Based in San Francisco or willing to relocate.

## Nice to Have

- Experience buying or managing data collection, annotation, or other human-in-the-loop services.
- Familiarity with robotics, egocentric video, wearable capture systems, or AI training data.
- Experience building supplier networks across multiple countries.
- Experience hiring or leading a small operations team.
- SQL, scripting, or automation skills that help improve reporting and operational workflows.

## Benefits

- Health insurance and a 401(k).
- Company-provided breakfast, lunch, dinner, and snacks.
- Covered Uber rides home.

This role is based at our San Francisco office, five days per week, with travel to partner operations as needed.

## About Sieve

## Company Overview
- **One-liner**: Sieve is an AI research lab and platform focused on building high-quality multimodal data (video, audio, image, and interaction data) and infrastructure for training frontier AI models.
- **Entity Type**: Private (Seed-stage)
- **Headquarters**: San Francisco, California, USA
- **Founded**: 2022
- **Founders**: Mokshith Voodarla (CEO) and Abhinav "Abhi" Ayalur (CTO)

## Core Business
- Primary industry: Artificial Intelligence / Data Infrastructure / Computer Vision
- Target customers: Frontier AI labs, Fortune 100 companies, and fast-growing AI startups working on generative media, robotics, computer use, world models, and agentic systems (primarily B2B Enterprise).
- Mission statement: To build the data and environments that frontier AI labs use to train the next generation of multimodal systems.

## Products & Services
- **Sieve Platform (sievedata.com)**: A development platform to discover, design, and run AI features at scale. It offers pre-built, production-ready apps and models (e.g., `sieve/speech_transcriber` for transcription, `sieve/seamless_text2text` for translation) that can be used via a single API call. The platform provides no-code interfaces, reliable infrastructure, and primitives like queues and async jobs. It is focused on making it easy to combine multiple AI models into complex applications (e.g., video dubbing, translation). [docs.sievedata.com]
- **Sieve Data Lab (sieve.ai)**: A multimodal data lab offering high-quality video, audio, image, and interaction datasets for frontier AI. Services include custom data collection, indexing billions of data points, filtering for semantics and rights, adding dense annotations (transcripts, object labels, UI events), and secure delivery with end-to-end encryption and SOC 2 Type 2 compliance. [sieve.ai]
- **Video AI API (Beta)**: A recently launched API that allows developers to use Sieve's pre-built AI apps and models for video processing in a single call. [sievedata.com]

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed.
- **Key Metric**: Raised approximately **$4M** in a seed round in 2022. [ycombinator.com, sievedata.com]
- **Notable Investors/Partners**: Y Combinator (Winter 2022 batch, with Diana Hu as Primary Partner), AI Grant (Nat Friedman & Daniel Gross). [ycombinator.com, sieve.ai/about]
- **Growth Signals**: The company has evolved from a general AI platform to a specialized research lab focusing on the critical bottleneck of training data for multimodal AI. It has attracted the trust of "frontier AI labs, Fortune 100 companies, and fast-growing AI startups." The team size is listed as 18 on Y Combinator (2022) and they are actively hiring for multiple engineering roles through the end of 2026, indicating scaling. [ycombinator.com, jobs.ashbyhq.com]

## Competitive Advantages
- **Focus on Data as a Moat**: Sieve is explicitly structured as a "research lab exclusively focused on video data," identifying that high-quality training data is the primary bottleneck for the next generation of AI (video, audio, robotics, agentic systems). [ycombinator.com]
- **End-to-End Data Service**: They provide a complete pipeline from custom collection and indexing to dense annotation and secure delivery, unlike many competitors who only offer one piece.
- **Deep Research Partnerships**: The team works directly with leading AI researchers to understand model bottlenecks and design high-signal datasets, creating a tight feedback loop between research needs and data production.
- **Strong Founder-Market Fit**: Founders Mokshith Voodarla (Scale AI, NVIDIA) and Abhinav Ayalur (NVIDIA, Niantic) have direct experience in building computer-vision systems and experiencing the data difficulties first-hand.

## Strategic Focus
- **Deliver Training Data for Frontier AI**: Sieve’s current priority is to scale its exabyte-scale infrastructure and novel multimodal understanding techniques to create datasets for video, audio, images, software, robotics, and interactive worlds. [sieve.ai/about]
- **Enable Complex AI Use Cases**: The platform side focuses on making it easy for developers to combine multiple models to build production-ready AI features (like translation, dubbing) quickly.
- **Data Security and Compliance**: Emphasizing secure, compliant data delivery with SOC 2 controls is a key priority for servicing Fortune 100 companies.

## Why Work Here
- **Culture**: The company describes itself as "tight-knit, fast-moving, and deeply customer-oriented." It is a "research lab to the core," combining frontier research with infrastructure and customer partnership. [sieve.ai/about]
- **Team**: The team brings together experience from NVIDIA, Scale AI, Zoox, and Niantic, providing exposure to top-tier expertise in AI and infrastructure. [sieve.ai/about]
- **Impact**: Employees will be working on the critical layer of data for the next generation of AI models (generative media, robotics, agents), offering a rare position at the forefront of AI research. [ycombinator.com]
- **Remote/Hybrid/Office**: The company is based in San Francisco, CA.
- **Open Roles**: As of mid-2026, they are actively hiring for **Applied Research Engineer**, **Distributed Systems Engineer**, **Product Engineer**, and **Software Engineer**, with salary ranges listed as $150K - $300K depending on role and experience. [jobs.ashbyhq.com, ycombinator.com]

## Sources
1. [docs.sievedata.com](https://docs.sievedata.com/guide/intro)
2. [jobs.ashbyhq.com](https://jobs.ashbyhq.com/sieve)
3. [sieve.ai](https://www.sieve.ai/)
4. [sieve.ai/about](https://www.sieve.ai/about)
5. [ycombinator.com](https://www.ycombinator.com/companies/sieve)

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