merlinlabs - Merlin Labs - Data Loop Pipeline Engineer
Requirements
• Degree in Computer Science, Artificial Intelligence, Data Science, Computer Engineering, Applied Math, or a related subject. • 3+ years in data engineering, with production ownership of pipelines feeding ML training. • Strong Python and SQL; solid grasp of data modeling, storage formats and processing frameworks. • Experience with dataset versioning and lineage tooling. • Comfort with high-volume time-series and multimodal sensor data — telemetry, video, audio, structured logs. • Care about correctness. In this role a quiet data bug becomes a model behavior nobody can explain. • Robotics, autonomous vehicle or aerospace data experience. • Familiarity with flight data formats and avionics bus data. • Experience building internal tools that engineers actually chose to use. • Data governance or provenance work in a regulated environment. • We welcome remote applicants for this role, with a preference for candidates based in or willing to relocate to Boston, MA for a hybrid work schedule at our HQ. • Merlin Labs offers an innovative, entrepreneurial, and team-focused startup environment. We also offer a top-notch benefits package (health, dental, life, flexible paid time off, and 401k with match) and work/life integration. Being part of the Merlin team allows you to become part of a small team that supports professional development while working together to achieve our mission.
Responsibilities
• Build and operate ingestion pipelines for flight test, simulation and operational data, including format normalization, time alignment across sources, and quality validation at the gate. • Implement dataset curation and versioning with full lineage: what went into a dataset, from where, processed how, and by which version of which tool. • Build automated mining and triage for the rare and interesting — anomalies, disagreements between learned and rule-based systems, near-boundary events — so the flywheel prioritizes signal over volume. • Own labeling workflows and tooling, including quality control and inter-annotator agreement where human labeling is involved. • Close the loop: instrument deployed-system behavior so that operational signal reliably reaches the next training cycle without manual shepherding. • Work with Flight Test & Operations on logging and instrumentation requirements, and help resolve access constraints where data is captured by third-party systems. • Monitor pipeline health and dataset coverage; alert on drift, gaps and silent breakage.
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