Data Engineer (Detect & Track Distillation)

The role

You will own the data layer that feeds ML models by turning raw, unstructured data into curated, versioned, training-ready datasets. You will manage terabytes of data and build ingestion pipelines, perform multimodal alignment, and handle dataset construction.

What you will do

• Ingest, decode, and store raw, unstructured field data from field logs into efficient, controlled formats.
• Align multiple data streams temporally and spatially.
• Transfer ingested data and public datasets into high-value data through parsing, filtering, de-duplication and revision.
• Define data gathering and labeling requirements and own the dataset-construction workflow and labeling tooling.
• Coordinate with teams responsible for data gathering and labeling.
• Build task-specific datasets for training and evaluation needs.
• Version datasets and maintain lineage for reproducible training runs.
• Store data in efficient, training-ready formats and manage storage tiering.
• Deliver clean, documented datasets and loading tools to prevent I/O-bound training.

Required qualifications

• A degree in a STEM field, or equivalent practical experience.
• Built and maintained pipelines for unstructured data at scale (video, images, or sensor data).
• Strong in Python and data engineering.
• Comfortable optimizing data loaders for common training frameworks (for example PyTorch).
• Systematic, quality-minded, pragmatic, and service-oriented.
• 100% dedication to Harmattan AI's mission.

Nice to have

• Multimodal sensor data
• labeling or dataset construction for ML
• dataset versioning tooling
• distributed data processing tooling

About the company

Harmattan AI is a next-generation defense prime building autonomous and scalable defense systems. The company is expanding its teams to deliver mission-critical systems to allied forces.