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Forward Deployed Engineer

San Francisco,...
V

Velvet

Startup
Category
Technical
Experience
0-3 years
Type
Full-Time
Location
San Francisco, CA, US
Salary
$175,000 - $200,000
Job Description
Benefits & Culture
Visa sponsorship
Core Values
Scrappy
Wear multiple hats
High bar for quality
Engineering mindset
This goes straight to the founder
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No recruiters. Founders reply directly.

Founder Signals
Response Rate
85%
Avg Response Time
2 hours
Compensation Calculator
In startups, higher salary usually means lower equity.
Salary (affects equity %)
Link salary ↔ equity
$125,000
$175,000$200,000
Equity % (auto from trade-off model)
1.19%
0%5%
Projected Exit Value
$350,000,000
$10M$500M
Live Trade-off
Salary
Equity %
Est. Equity Value at Exit
$100,000
1.19%
$2,082,500
$125,000
1.19%
$2,082,500
$150,000
1.19%
$2,082,500
$175,000
1.19%
$2,082,500

Advanced Salary & Equity Calculator

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Skills

Operations, Python, SQL, Claude Code

Velvet is a data research company founded by Lucas Mantovani (ex Meta FAIR) and Lucas Tucker (ex Adobe). Our mission is to make AI more human by producing high quality audiovisual datasets for frontier labs.

We are hiring a Forward Deployed Engineer to sit at the intersection of our platform and the real-world operations that power it. This is a hands-on, execution-focused role. You will own the end-to-end lifecycle of getting people onto our platform, procuring the data we need, and writing the scripts that turn collected footage into clean, usable training data.

What you'll do

  1. Own data procurement: identify, recruit, and qualify participants for active data collection projects.
  2. Meet with researchers from top labs to build the highest quality video datasets for them.
  3. Write and maintain post-processing scripts that clean, validate, and package thousands of hours of video data for training world models.
  4. Identify and resolve operational issues — failed video uploads, payment problems, etc
  5. Build lightweight internal tools and automations to reduce manual work and increase throughput as we scale.

Who you are

  1. A technically savvy generalist with impressive professional or academic accomplishments, comfortable writing data pipelines, making deals, and meeting with top researchers.
  2. Someone who gets things done
  3. Detail-oriented and reliable when managing people and data at scale, where errors have downstream consequences.
  4. Comfortable working in ambiguous, fast-moving environments

Even better if you have

  1. Background in research operations, data labeling platforms, or data collection.
  2. Experience building large-scale data processing pipelines.
  3. Background in ML research.

You will thrive in this role if

  1. You are energized by operational work that has immediate, visible impact.
  2. You treat broken processes as engineering problems worth solving properly.
  3. You hold yourself to a high bar for data quality, knowing this determines model performance.