{"id":2744314,"url":"https://alion.io/job/reality-defender-staff-data-platform-engineer","title":"Staff Data Platform Engineer","company":{"id":63361,"name":"Reality Defender","domain":"realitydefender.com","url":"https://alion.io/company/reality-defender","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":210000,"max":260000,"currency":"USD","period":"year","gross":null,"usd_annual":260000},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Dagster","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"IAM","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Python","optional":false},{"name":"Ray","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Synthetic Data","optional":false},{"name":"Terraform","optional":false},{"name":"Text-to-Speech","optional":false}],"status":"live","first_seen_at":"2026-10-16T18:48:43Z","employer_posted_date":"2026-10-16","last_verified_at":"2026-10-17T15:19:53Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Staff Data Platform Engineer\nLocation: NYC HQ or Remote (U.S.)| Full-time | Engineering\nWho we are.\nReality Defender is an award-winning cybersecurity company helping enterprises and governments detect deepfakes and AI-generated media. Utilizing a patented multi-model approach, Reality Defender is robust against the bleeding edge of generative platforms producing video, audio, imagery, and text media. Reality Defender's API-first deepfake detection platform empowers teams and developers alike to identify fraud, disinformation campaigns, and harmful deepfakes in real time.\nBacked by world class investors including DCVC, Illuminate Financial, Y Combinator, Booz Allen Hamilton, IBM, Accenture, Rackhouse, and Argon VC, Reality Defender works with leading enterprise clients, financial institutions, and governments in order to ensure AI-generated media is not used for malicious purposes.\nYoutube: Reality Defender Wins RSA Most Innovative Startup\nThe Staff Data Platform Engineer Role.\nReality 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:\nOwn 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.\n\nComplete 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.\n\nBuild reusable infrastructure for in-house synthetic data generation, so researchers can produce new deepfake variants across modalities on demand instead of one-off.\n\nMake 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.\n\nOwn pipeline reliability, observability, and processing cost per dataset as core metrics of the platform.\n\nPartner with ML researchers to understand their data needs and turn them into self-serve tools that speed up model iteration.\n\nMentor engineers and raise the bar on data engineering practices: code review, testing, documentation, and runbooks.\n\nWork with Security and compliance stakeholders to make sure data handling, licensing, and access controls meet the standards our enterprise and government clients expect.\n\nHelp shape the long-term data platform roadmap with engineering and research leadership.\n\nWho you are.\n8+ 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.\n\nDeep 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).\n\nProduction experience with Databricks, Unity Catalog, Delta Lake, and Spark on AWS, including performance tuning, access controls, and operational troubleshooting.\n\nExperience working with large unstructured media such as video, audio, or images, including the realities of large files, decoding and transcoding, and metadata at scale.\n\nA track record of building reproducible ML datasets: versioning, lineage, data quality validation, and orchestration (Airflow, Dagster, Databricks Workflows, or similar).\n\nStrong Python and SQL, and the judgment to own ambiguous platform problems end-to-end on a lean team.\n\nOwn infrastructure and deployment automation using Terraform and CI/CD, including AWS storage, IAM, compute, Databricks resources, and distributed processing environments.\n\nExperience building synthetic data generation pipelines or running generative models (diffusion, voice cloning/TTS, video generation) at scale. (nice to have)\n\nBackground supporting ML research teams with training and evaluation data, especially for multimodal models. (nice to have)\n\nExperience 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)\n\nWithin 12 months, you'll…\nOwn a mature, self-serve data platform that researchers use to create, version, and export datasets without waiting on platform support.\n\nHave scaled synthetic data generation across vision, audio, and multimodal research, broadening our detection coverage of new generative techniques.\n\nDeliver reproducible evaluation datasets that let the company compare model versions with confidence.\n\nBe setting the multi-year data platform roadmap and leading high-leverage initiatives beyond the original scope.\n\nWhat we offer.\nReality Defender offers the following benefits to all our employees, regardless of location:\nHealthcare plans with 100% premium coverage for employees and partial coverage available for dependents\n\nDental and Vision plans with 100% premium coverage for employees and their dependents\n\nShort/Long-term disability and life insurance plans with 100% premium coverage for employees\n\nFSA/HSA and 401k programs\n\nEquity compensation\n\n20 days of PTO per year\n\n12 weeks of Parental Leave\n\nLearning and Development budget\n\nMonthly wellness benefits\n\nAnnual company-sponsored offsite\n\nFor employees working from Reality Defender's HQ in NYC, we offer the following benefits:\nDaily in-office lunch through UberEats\n\nCommuter benefits\n\nRemote Fridays\n\nHappy Hours and other local events\n\nBase salary range: 210,000 - 260,000, based on experience, level, and location. 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