Technical Staff Member – Data Intelligence

Reka AI

Technical Staff role at Reka working with researchers and engineers to ensure data quality for ML. Building processing pipelines and optimizing data systems for model training.

Posted 5/5/2026full-timeRemote • 🇺🇸 United StatesLeadWebsite

Tech Stack

Tools & technologies

AirflowOpen SourcePythonPyTorchRaySpark

About the role

Key responsibilities & impact

Work with model researchers to define what “good data” means for our models, including quality metrics, validation checks, and acceptance thresholds
Explore open source datasets and create internal ones most suitable to build fundamental 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 so experiments are reproducible and it’s clear what data went into which training and evaluation runs
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

Requirements

What you’ll need

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

Benefits

Comp & perks

Flexible work arrangements

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningdeep learningdata quality assessmentdata domain mixturesdomain adaptationdistributed processingorchestrationPythonPyTorchSpark

Soft Skills

analytical skillscommunicationprioritizationcollaborationexperiment designproblem-solvingadaptabilityattention to detailresearch experienceunbiased outcomes