Lead Data Intelligence Engineer — Scalable ML Pipelines

Reka; United States; Remote; USD 120,000 - 210,000; Full time

Benefits offered by this job

5 weeks paid leave

Comprehensive health benefits (vision,

Dental

Visa support

Job summary

Reka, a globally distributed foundation model startup headquartered in the San Francisco Bay Area, seeks a data-focused engineer to ensure high-quality data at petabyte scale. You’ll collaborate with researchers and engineers to define good data, build pipelines, and run compute behind model training and evaluation.

You’ll move between research questions and production, developing automated quality assessments, lineage tracking, and scalable data tooling in a remote-first environment.

Qualifications

• Experience with large-scale data and compute systems.
• Ability to run analyses and ship reliable systems.
• Experience with distributed processing/orchestration (Spark/Ray/Airflow or equivalents).
• Familiarity with data quality, provenance, and dataset releases.
• Strong Python skills and experience with model training workflows.

Responsibilities

• Define what constitutes good data with quality metrics and acceptance thresholds.
• Explore open source datasets and create internal ones for World Models.
• Build algorithms for automated data quality assessment and domain adaptation.
• Track datasets, metadata, provenance, and versions for reproducibility of experiments.
• Own CI/CD and tooling for the data stack (GitHub, Python, PyTorch) and automate workflows.
• Monitor throughput, storage, and compute utilization across pipelines.

Skills

ML fundamentals

Deep learning

Python

Data analysis

Experiment design

Tools

Spark

Ray

Airflow

PyTorch

GitHub

Job description

Reka, a globally distributed foundation model startup headquartered in the San Francisco Bay Area, seeks a data-focused engineer to ensure high-quality data at petabyte scale. You’ll collaborate with researchers and engineers to define good data, build pipelines, and run compute behind model training and evaluation.

You’ll move between research questions and production, developing automated quality assessments, lineage tracking, and scalable data tooling in a remote-first environment.