Jobs / United States / Skdse

Skdse

Data Operations & Labeling Specialist (All Genders)

Location unlisted Posted today

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AgileData engineeringMachine learningCommunicationPythonSQLEnglish

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Sponsorship verdict

Posting rules out sponsorship

The posting rules out sponsorship or requires citizenship or security clearance.

  • No government sponsor record hereThis employer posted directly and does not match a government sponsor register.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • Security clearance mentionedFrom the posting’s own wording.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

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Before you apply

Requirement gap

The posting mentions a security clearance — usually restricted to citizens of that country.

Sponsorship unknown

No register record and no sponsorship wording in the posting. Worth asking the employer before investing significant time.

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About the role

At Stark, we forge the future of European and national security through cutting-edge, AI-driven technology and unmatched engineering precision. As a premier defence technology company, our mission is clear: to equip NATO Allies and their partners with next-generation autonomous defence platforms and advanced AI-driven software built to perform in the world’s most demanding environments. We believe that true security stems from relentless innovation. By combining elite engineering talent with agile technology and an AI-native operational culture, Stark turns complex defence challenges into field-tested, multi-domain solutions. WHY JOIN US • The software and systems you work on directly protect personnel and defend European and national sovereignty. • You will work alongside industry-leading minds on autonomous systems, advanced propulsion, and secure cyber platforms. • We foster a fast-paced, collaborative environment where bold ideas are supported by serious R&D backing. ABOUT THE TEAM The Data Operations team at Stark builds and maintains the core data pipelines, sensor logging, and annotation workflows that feed our AI and perception models. Operating at the intersection of hardware testing, flight logs, and machine learning, the team ensures high-throughput, high-fidelity data availability. We work closely with ML Engineers, perception experts, and external labeling partners to scale training data for autonomous defence systems. YOUR MISSION You are the crucial bridge between our raw field data, our external labeling partners, and our internal Machine Learning teams. Your mission is to ensure our AI models are trained on the highest quality data possible. You will own the day-to-day operations of the data labeling lifecycle: curating raw data, preparing annotation batches, managing vendor communication, and rigorously assessing the quality of incoming labels. If you are highly organized, detail-oriented, and interested in the intersection of data operations and Computer Vision, this is the perfect place to start your career in AI. WHAT YOU WILL DO AT STARK • Own the day-to-day data labeling lifecycle: curate raw field data, create annotation batches, and prepare deliveries for external labeling companies. • Serve as the primary point of contact for external data annotation vendors, clarifying edge cases and providing feedback on labeling guidelines. • Conduct rigorous Quality Assurance (QA) assessments on incoming label deliveries, track error rates, and create performance reports. • Support data curation efforts, filtering and selecting the most valuable sensor data (images, video, lidar) for model training. • Work closely with ML Engineers to understand their data needs, edge cases, and specific Computer Vision requirements. • Help maintain the data catalog by ensuring incoming datasets are properly tagged and logged. WHAT YOU BRING TO THE MISSION • Highly organized and detail-oriented: you can manage multiple data batches, vendor deliveries, and QA processes simultaneously without dropping the ball. • Strong communication skills: you are comfortable coordinating with external vendors and writing clear, unambiguous instructions/guidelines. • Basic understanding of Computer Vision and Machine Learning concepts (e.g., bounding boxes, segmentation masks, object tracking). • Comfortable with basic scripting (Python) and data querying (SQL) to automate small tasks or filter data batches. • Pragmatic problem-solver who enjoys bringing order to chaotic data deliveries. • Fluent in English. If you're interested in building the future of European Defence with us, and you see yourself reflected on the description above, please send us your CV in English . We're looking forward to meeting you! SECURITY CLEARANCE

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