21 hours ago
Base Salary
$150k - $225k/yr
Responsibilities
- Launch and scale hardware and data-collection deployments across different countries.
- Set up camera rigs, local infrastructure, software systems, and reliable data-upload workflows.
- Write code, debug unfamiliar systems, and ship practical solutions quickly.
- Work with site partners, engineers, and local operators to resolve deployment issues.
- Train local engineers and build local technical teams through candidate identification, interviewing, and onboarding.
- Turn field learnings into better software, deployment tools, and repeatable launch processes.
- Support local operations as needed to get sites running.
Requirements
- Strong computer science fundamentals through a CS degree or equivalent practical experience.
- Software engineering ability with evidence of independently building and shipping practical solutions; a couple of years of experience is preferred, while exceptional recent graduates are welcome.
- Ability to work across software, hardware, networking, and data uploads and learn unfamiliar systems quickly.
- Strong communication and interpersonal skills for working with site partners and training people with varying technical experience.
- Ability to take ambiguous goals, determine required actions, and follow through independently.
- Based in San Francisco and willing to spend 75%–85% of the time traveling globally.
- Preferred experience includes cameras, embedded systems, Linux, networking, large data transfers, hiring or onboarding technical teams, international project launches, early-stage startups, or multiple languages.
Benefits
- 401(k) and full health insurance.
- Breakfast, lunch, dinner, and snacks covered.
- Ubers home covered.
- Based in San Francisco with 75%–85% global travel required.
About Sieve
Sieve builds datasets and infrastructure for training video AI models, combining large-scale video processing with novel video understanding techniques. Its tools support ML teams working on media, gaming, AR/VR, and robotics by supplying high-quality video training data and pipelines. Founded in 2016 and headquartered in Palo Alto, the company operates as a privately held AI lab focused exclusively on video data.