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Staff Data Platform EngineerReality Defender
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  • Location: United States
  • Workplace: Remote
  • Job type: Full Time
  • Salary: $210-260K/year
  • Posted: Posted

  • Own end-to-end data platform for AI research ingestion and processing
  • 8+ years building data infrastructure with Databricks and Spark
  • Experience with synthetic data generation and unstructured media is a plus
  • Remote within the U.S., $210K-$260K base salary
Staff Data Platform Engineer

Location: NYC HQ or Remote (U.S.)| Full-time | Engineering

Who we are.

Reality Defender is an award-winning AI company that develops models to help enterprises and governments tell what’s real from what’s AI-generated. Our multi-model platform detects AI-generated video, audio, and images in real time, and stays robust against new generative tools as they emerge.

The question our customers are asking is changing. It’s no longer only “is this a deepfake?” It’s “is this real, and is it who it claims to be?” Every day, organizations ask us:

  • “Is the voice on this call a real person?”

  • “Is that video of our CEO real?”

  • “Is everyone in this meeting who they say they are?”

We answer those questions in real time, across video, audio, images, and text, so security teams can act before the damage is done.

Reality Defender is backed by world-class investors including DCVC, Illuminate Financial, Y Combinator, Booz Allen Hamilton, IBM, Accenture, Rackhouse, and Argon VC. We work with leading enterprises, financial institutions, and government agencies to make sure AI-generated media can’t be used to deceive.

 

Youtube: Reality Defender Wins RSA Most Innovative Startup

The Staff Data Platform Engineer Role.

Reality Defender's detection models are only as strong as the data behind them, and every new generative tool raises the bar on the volume and variety of media we need to train and evaluate against. The Staff Data Platform Engineer will own the shared AI data platform behind our vision, audio, and multimodal research, turning acquired and internally generated image, video, audio, and text data into reliable, reproducible datasets, from continuous ingestion through processing, governance, and export. This is a senior, hands-on role where you'll complete our Databricks and distributed processing platform and build the reusable infrastructure behind our in-house synthetic data generation, including producing the very deepfakes our models learn to catch. This is a full-time role, reporting to our Director of Data. Responsibilities include:

  • Own the end-to-end data platform for AI research: continuous ingestion, preprocessing, governance, and export of image, video, audio, and text data at high volume.

  • Complete and scale our Databricks lakehouse and distributed processing stack (Spark, Ray, or similar), making architecture and build-vs-buy decisions that hold up as data volume grows.

  • Build reusable infrastructure for in-house synthetic data generation, so researchers can produce new deepfake variants across modalities on demand instead of one-off.

  • Make every dataset reproducible and traceable through versioning, lineage, metadata, quality checks, and stable train/eval splits, so any model result can be tied back to the exact data behind it.

  • Own pipeline reliability, observability, and processing cost per dataset as core metrics of the platform.

  • Partner with ML researchers to understand their data needs and turn them into self-serve tools that speed up model iteration.

  • Mentor engineers and raise the bar on data engineering practices: code review, testing, documentation, and runbooks.

  • Work with Security and compliance stakeholders to make sure data handling, licensing, and access controls meet the standards our enterprise and government clients expect.

  • Help shape the long-term data platform roadmap with engineering and research leadership.

Who you are.

  • 8+ years building data platforms or data infrastructure, including staff- or lead-level ownership of production pipelines that generate, ingest, or deliver data at high volume.

  • Deep hands-on experience with distributed processing (Spark, Ray, or similar) and lakehouse platforms, ideally Databricks, on top of cloud object storage (S3, GCS, or Azure Blob).

  • Production experience with Databricks, Unity Catalog, Delta Lake, and Spark on AWS, including performance tuning, access controls, and operational troubleshooting.

  • Experience working with large unstructured media such as video, audio, or images, including the realities of large files, decoding and transcoding, and metadata at scale.

  • A track record of building reproducible ML datasets: versioning, lineage, data quality validation, and orchestration (Airflow, Dagster, Databricks Workflows, or similar).

  • Strong Python and SQL, and the judgment to own ambiguous platform problems end-to-end on a lean team.

  • Own infrastructure and deployment automation using Terraform and CI/CD, including AWS storage, IAM, compute, Databricks resources, and distributed processing environments.

  • Experience building synthetic data generation pipelines or running generative models (diffusion, voice cloning/TTS, video generation) at scale. (nice to have)

  • Background supporting ML research teams with training and evaluation data, especially for multimodal models. (nice to have)

  • Experience in security, fraud, trust & safety, or another adversarial domain, or at a Series A or B startup where scope regularly outpaces headcount. (nice to have)

Within 12 months, you'll…

  • Own a mature, self-serve data platform that researchers use to create, version, and export datasets without waiting on platform support.

  • Have scaled synthetic data generation across vision, audio, and multimodal research, broadening our detection coverage of new generative techniques.

  • Deliver reproducible evaluation datasets that let the company compare model versions with confidence.

  • Be setting the multi-year data platform roadmap and leading high-leverage initiatives beyond the original scope.

What we offer.

Reality Defender offers the following benefits to all our employees, regardless of location:

  • Healthcare plans with 100% premium coverage for employees and partial coverage available for dependents

  • Dental and Vision plans with 100% premium coverage for employees and their dependents

  • Short/Long-term disability and life insurance plans with 100% premium coverage for employees

  • FSA/HSA and 401k programs

  • Equity compensation

  • 20 days of PTO per year

  • 12 weeks of Parental Leave

  • Learning and Development budget

  • Monthly wellness benefits

  • Annual company-sponsored offsite

For employees working from Reality Defender's HQ in NYC, we offer the following benefits:

  • Daily in-office lunch through UberEats

  • Commuter benefits

  • Remote Fridays

  • Happy Hours and other local events

Base salary range: 210,000 - 260,000, based on experience, level, and location. Role includes equity.

Apply now

About the job

Location

United States

Job type

Full Time

Workplace

Remote

Experience

Senior

Department

Engineering

First posted on

Salary

$210-260K/year
Reality DefenderReality Defender

Award-Winning Deepfake Detection and Protection

Company size

51-200 employees

Founded in

2021

Industry

Computer and Network Security

Headquarters

New York

Social media

Company profileVisit realitydefender.com

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