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Merlin Labs (NASDAQ: MRLN) is a publicly traded aerospace and defense company building autonomous flight systems. The company has proven its non-human pilot autonomy platform through hundreds of autonomous flights and is expanding to accelerate development and deployment across commercial and defense aviation.
In this role, you will own the data infrastructure that transforms flight test, simulation, and operational data into trustworthy, versioned training datasets for Merlin's autonomy platform. You will be responsible for building and operating ingestion pipelines that handle format normalization, time alignment across multiple sources, and quality validation. Key responsibilities include:
- Design and maintain production ingestion pipelines for flight test, simulation, and operational data with format normalization, time alignment, and quality gates
- Implement dataset curation and versioning systems with complete lineage tracking (source, processing steps, tool versions)
- Build automated systems to identify and triage rare, interesting signals—anomalies, system disagreements, boundary events—to prioritize signal over volume
- Own labeling workflows and tooling, including quality control and inter-annotator agreement metrics
- Close the feedback loop by instrumenting deployed systems so operational data reliably feeds back into training cycles without manual intervention
- Collaborate with Flight Test & Operations teams on logging requirements and resolve data access constraints from third-party systems
- Monitor pipeline health, dataset coverage, and alert on drift, gaps, and silent failures
You will work in an on-site environment at Merlin's Boston headquarters with catered lunches, snacks, and beverages provided.
QUALIFICATIONS:
- Degree in Computer Science, Artificial Intelligence, Data Science, Computer Engineering, Applied Math, or related field
- 3+ years of data engineering experience with production ownership of pipelines feeding ML training systems
- Strong Python and SQL skills; solid understanding of data modeling, storage formats, and processing frameworks
- Experience with dataset versioning and lineage tooling
- Comfort working with high-volume time-series and multimodal sensor data (telemetry, video, audio, structured logs)
- Strong commitment to data correctness and quality
NICE TO HAVE:
- Robotics, autonomous vehicle, or aerospace data experience
- Familiarity with flight data formats and avionics bus data
- Experience building internal tools that engineers actively adopt
- Data governance or provenance work in regulated environments
