出海雷达

洛杉矶高级软件工程师(数据平台,远程)

Senior Software Engineer, Data Platform (Los Angeles/Remote)

开发工程限定地区(需当地身份)
公司Rheaction
薪资$200,000 - $240,000/年
工作地点United States
地域资格限定地区(需当地身份)
时区要求日间重叠约 9 小时,基本正常作息
用工类型Full Time
发布时间4 天前
数据来源Himalayas
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注意地域限制:该职位明确限定在 United States 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

Location: Remote — Los Angeles area preferred
Employment: Full-time
Experience: 5–8 years
Compensation: $200,000–$240,000 + 0.25%–0.5% equity
Work Authorization: U.S. citizenship required
About the Role
We're looking for a Senior Software Engineer, Data Platform to build and own a data platform from the ground up.
This is a highly autonomous, zero-to-one role focused on turning large volumes of complex, real-world data into clean, consistent, and reliable datasets for machine learning and product teams.
You'll architect high-throughput pipelines, establish data quality and reproducibility standards, and build the infrastructure and tooling needed to make data easy to discover, process, label, and use.
What You'll Do

  • Architect and build high-throughput data pipelines from scratch.
  • Develop pipelines for processing, aligning, transforming, and calibrating complex datasets.
  • Build backfill and reprocessing frameworks for historical data.
  • Establish dataset lineage, versioning, and reproducibility.
  • Build APIs and tooling for dataset discovery and access.
  • Develop data-quality metrics, monitoring, and alerting.
  • Optimize storage, compression, partitioning, and data access patterns.
  • Build internal tools and workflows for ML and data-labeling teams.
  • Partner closely with ML engineers to understand and support their data requirements.

What We're Looking For

  • 5–8 years of software or data engineering experience.
  • Proven ability to architect a data platform or high-throughput pipeline from a blank page.
  • Strong Python and data tooling experience, such as PyArrow, Polars, Pandas, NumPy, or SciPy.
  • Experience with AWS or another major cloud platform and deploying production data pipelines.
  • Experience with a services language such as Go, Rust, or TypeScript.
  • Strong understanding of data lineage, versioning, reproducibility, and data quality.
  • Experience building backfill and reprocessing systems.
  • High ownership and ability to operate independently in a startup environment.
  • U.S. citizenship required.

Strong Plus

  • Founding or early data-platform engineering experience.
  • Experience with sensor, audio, video, telemetry, or geospatial data.
  • Airflow, Prefect, MLflow, W&B, or similar tooling.
  • Experience building labeling tools or ML data workflows.
  • Strong full-stack/generalist capabilities.
  • Experience treating datasets as a product, with strong documentation and discoverability.

Originally posted on Himalayas

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