---
title: 'Strategic Partnerships & Ops Lead, Physical AI at Sieve'
canonical: 'https://feeny.ai/job/strategic-partnerships-ops-lead-physical-ai-sieve-san-francisco-399z6fq1nh8x'
type: 'job'
last_seen: '2026-10-15'
---

# Strategic Partnerships & Ops Lead, Physical AI at Sieve

- **Company:** Sieve
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-10-05
- **Last confirmed live:** 2026-10-15
- **Apply:** https://jobs.ashbyhq.com/sieve/b4947fec-dcf6-4f37-8641-60de801f1230

## Job description

## About Us

Sieve is a multimodal lab curating the world’s highest-quality training datasets, spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure with novel multimodal understanding techniques to push the frontier of foundation models. We exist to solve one of the biggest bottlenecks in AI: high-quality training data. We partner with top AI labs and did $XXM last quarter alone, with a team of roughly 40 people. We raised our Series A from firms including Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.

## Why Now

Physical AI needs data from real industrial environments — factories, manufacturing lines, and operations that don’t show up on the open web. Unlocking that access, and running the ops that turn it into lab-grade data, is a core growth constraint. You’ll join early enough to build both the partnerships and the operating system behind them.

## About the Role

This role mixes industrial partnerships with hands-on data ops. You’ll open doors into factories and similar environments, then run the workforce, QA, and platform work that turns that access into reliable multimodal data for frontier labs. Strong fits look like industrials consultants, robotics operators, PE ops folks, or early ops hires who’ve already managed human-in-the-loop work and know how to earn trust with plant leaders and ops teams.

## What You’ll Do

- Open industrial access: Identify, pitch, and close partnerships with factories, manufacturers, and industrial operators; navigate security and compliance from first intro through live collection.
- Operate the data ops platform: Run workforce management, task assignment, and QA workflows; build SOPs and training so quality stays at the bar frontier labs require.
- Grow supply and partnerships: Source, onboard, and manage a distributed workforce for annotation, curation, and review; test acquisition and sourcing channels that scale.
- Own product ops with engineering: Ship tooling improvements, track operational metrics, and close gaps in the data platform.
- Turn one-offs into systems: Document playbooks so partner wins and ops workflows repeat across sites and programs.

## Requirements

- Direct relationships into factories, manufacturing, or adjacent industrial environments — or a clear track record of building them
- Mixed technical and non-technical skillset; comfortable with data tooling, light scripting, and spreadsheet-level analysis
- Strong organizational skills and attention to detail; able to manage multiple concurrent work streams
- Growth mindset: experience running or contributing to user acquisition, sourcing campaigns, or platform growth
- Comfort with ambiguous, relationship-heavy work and the unglamorous ops needed to make a partnership live
- Bachelor’s in CS, STEM, or equivalent practical experience; in-person at our SF HQ

## Nice to Have

- Experience managing human-in-the-loop data operations or annotation pipelines
- At least 1 year of engineering experience or strong technical fluency
- Prior work inside manufacturing, robotics deployment, factory ops, PE portfolio ops, or as an early hire / AI-lab ops lead
- Familiarity with data quality frameworks, ML data pipelines, or physical AI

## Benefits

- 401(k) and full health insurance
- Breakfast, lunch, and dinner covered, plus your choice of snacks
- Ubers covered home

*All roles at Sieve require you to be onsite in San Francisco 5 days per week

## 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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