Data Intelligence Engineer, Scale-Out ML Data Pipelines

reka; Singapore; Remote; SGD 90,000 - 150,000; Full time

Job summary

Reka is a globally distributed foundation model startup, headquartered in the San Francisco Bay Area, California. Embracing a remote-first approach, our team brings together top talent from around the world.

Our founding team, along with many of our team members, has contributed to many of the breakthroughs in AI over the past decade. In this role, you’ll work with model researchers, data infrastructure engineers, and cross-functional partners to ensure data is high quality and can be produced

Qualifications

• Strong ML and deep learning fundamentals with experience building and operating large-scale data and/or compute systems.
• Comfortable moving between research questions and production engineering: you can dig into data, run analyses, and also ship reliable systems
• Demonstrated research experience with data compositions, quality, and dataset releases
• Ability to design and execute experiments with convincing unbiased outcomes
• Practical experience with distributed processing and orchestration (Spark, Ray, Airflow, or equivalents)
• Solid Python skills, and familiarity with the tooling around modern model training workflows (datasets, checkpoints, experiment tracking)
• Strong instincts around data quality: how to measure it, how to monitor it, and how to prevent regressions as things scale
• Able to work in a fast-moving environment, prioritize what matters, and communicate clearly with both researchers and engineers
• Bonus: experience with large video datasets, dataset curation for training, or building internal tooling for evaluation/analysis in ML environments

Responsibilities

• Define what “good data” means for our models, including quality metrics, validation checks, and acceptance thresholds
• Explore open source datasets and create internal ones suited for World Models
• Build algorithms for automated data quality assessment, data domain mixtures, and domain adaptation from synthetic to real data
• Track datasets, metadata, provenance, and versions for reproducible experiments
• Own CI/CD and development tooling for the data stack (GitHub, Python, PyTorch), and automate repetitive workflows to reduce friction
• Track and optimize throughput, storage, and compute utilization across pipelines and related assets

Skills

ML fundamentals

Python skills

Distributed processing

Experiment design

Data quality

Production engineering

Spark

Airflow

Ray

Tools

Spark

Ray

Airflow

GitHub

PyTorch

Job description

Reka is a globally distributed foundation model startup, headquartered in the San Francisco Bay Area, California. Embracing a remote-first approach, our team brings together top talent from around the world.

Our founding team, along with many of our team members, has contributed to many of the breakthroughs in AI over the past decade. In this role, you’ll work with model researchers, data infrastructure engineers, and cross-functional partners to ensure data is high quality and can be produced