Staff Data Platform Engineer

Reality Defender•New York, NY

2d•$210,000 - $260,000

About The Position

Reality Defender is seeking a Staff Data Platform Engineer to own the shared AI data platform supporting vision, audio, and multimodal research. The role turns acquired and internally generated image, video, audio, and text data into reliable, reproducible datasets through continuous ingestion, processing, governance, and export. This is a senior, hands-on position focused on completing the Databricks and distributed processing platform and building reusable infrastructure for in-house synthetic data generation, including deepfakes used to train detection models. The role reports to the Director of Data and partners with researchers, engineers, Security, compliance stakeholders, and leadership. The position is based at the NYC headquarters or remotely in the United States. It is full-time. The stated base salary range is $210,000–$260,000, based on experience, level, and location, and the role includes equity. Within 12 months, the engineer is expected to own a mature self-serve data platform for researchers to create, version, and export datasets; scale synthetic data generation across vision, audio, and multimodal research; deliver reproducible evaluation datasets; and help set the multi-year platform roadmap while leading high-impact initiatives.

Requirements

8+ years building data platforms or data infrastructure, including staff- or lead-level ownership of production pipelines that generate, ingest, or deliver high-volume data.
Deep hands-on experience with distributed processing such as Spark or Ray and lakehouse platforms, ideally Databricks, on cloud object storage such as 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 large files, decoding and transcoding, and metadata at scale.
Track record building reproducible ML datasets, including versioning, lineage, data quality validation, and orchestration with tools such as Airflow, Dagster, or Databricks Workflows.
Strong Python and SQL skills and the judgment to own ambiguous platform problems end-to-end on a lean team.
Experience owning infrastructure and deployment automation using Terraform and CI/CD, including AWS storage, IAM, compute, Databricks resources, and distributed processing environments.

Nice To Haves

Experience building synthetic data generation pipelines or running generative models such as diffusion, voice cloning/TTS, or video generation at scale.
Background supporting ML research teams with training and evaluation data, especially for multimodal models.
Experience in security, fraud, trust and safety, or another adversarial domain, or at a Series A or B startup where scope regularly outpaces headcount.

Responsibilities

Own the end-to-end AI research data platform, including continuous ingestion, preprocessing, governance, and export of high-volume image, video, audio, and text data.
Complete and scale the Databricks lakehouse and distributed processing stack, making architecture and build-versus-buy decisions that support growing data volumes.
Build reusable infrastructure for on-demand synthetic data generation across modalities.
Make datasets reproducible and traceable through versioning, lineage, metadata, quality checks, and stable train/evaluation splits.
Own pipeline reliability, observability, and processing cost per dataset as core platform metrics.
Partner with ML researchers to understand data needs and build self-serve tools that accelerate model iteration.
Mentor engineers and improve data engineering practices, including code review, testing, documentation, and runbooks.
Work with Security and compliance stakeholders to ensure data handling, licensing, and access controls meet enterprise and government client expectations.
Help shape the long-term data platform roadmap with engineering and research leadership.
Scale synthetic data generation across vision, audio, and multimodal research and deliver reproducible evaluation datasets.
Lead high-leverage data platform initiatives beyond the initial role scope.

Benefits

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- and long-term disability and life insurance plans with 100% premium coverage for employees.
FSA/HSA programs.
401(k) program.
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 NYC HQ employees: daily in-office lunch through UberEats, commuter benefits, remote Fridays, happy hours, and other local events.