
2 - 10 employees
Founded 2019
🎯 Recruiter
👥 HR Tech
Recruitment • HR Tech
Rheaction is a human-led, AI-powered recruiting firm that helps ambitious companies find exceptional talent and helps candidates discover impactful opportunities. The company combines recruiter expertise with AI-driven sourcing to search beyond active job boards, target passive candidates, and validate each candidate for experience, motivation, and fit. Rheaction serves high-growth startups, technology companies, and teams across diverse industries, and operates from offices in San Francisco, New York, and Denver while supporting clients worldwide.
🕒 October 30
Where this job comes from
Posted on Rheaction's careers page ↗, not through a job board
First seen by Remote Rocketship October 30
Still open on Rheaction's site. Checked 3 minutes ago.

2 - 10 employees
Founded 2019
🎯 Recruiter
👥 HR Tech
Recruitment • HR Tech
Rheaction is a human-led, AI-powered recruiting firm that helps ambitious companies find exceptional talent and helps candidates discover impactful opportunities. The company combines recruiter expertise with AI-driven sourcing to search beyond active job boards, target passive candidates, and validate each candidate for experience, motivation, and fit. Rheaction serves high-growth startups, technology companies, and teams across diverse industries, and operates from offices in San Francisco, New York, and Denver while supporting clients worldwide.
• 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
• 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
• 0.25%–0.5% equity
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