Staff Infra Engineer, ML Data Pipelines & GPUs

Sieve; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

401k

Health insurance

Meals & snacks

Uber rides home

Onsite SF HQ

Job summary

Sieve, a multi-modal lab, seeks an infrastructure engineer to design and run ML data pipelines and ETL systems at scale in San Francisco. You will focus on uptime, reliability, and cost efficiency while handling thousands of GPUs and complex workflows.

You’ll work with cloud architectures, build fast distributed systems, and create internal tooling and CI/CD for rapid iteration. This is an onsite role at our SF HQ.

Qualifications

• 3+ years of experience building foundational data infrastructure.
• Proficient in working across diverse cloud architectures.
• Pipelines that process petabytes of data.
• Developed robust CI/CD pipelines tailored for ML-focused teams.
• Strong coding experience with Go and Python; Rust is a plus.
• Operates as an IC who leads by example.
• Experience with large-scale video data systems.
• Onsite at SF HQ.

Responsibilities

• Design and engineer systems that handle compute, scheduling, and orchestration of ML+ETL pipelines.
• Prioritize uptime, reliability, and cost-efficiency for large-scale data workloads.
• Build internal tooling and CI/CD to accelerate model and data pipeline development.

Skills

Go

Python

Rust

Job description

Sieve, a multi-modal lab, seeks an infrastructure engineer to design and run ML data pipelines and ETL systems at scale in San Francisco. You will focus on uptime, reliability, and cost efficiency while handling thousands of GPUs and complex workflows.

You’ll work with cloud architectures, build fast distributed systems, and create internal tooling and CI/CD for rapid iteration. This is an onsite role at our SF HQ.