Data/ML Infrastructure Engineer

The role

This individual contributor will build systems that transform drone, airborne, orbital, and mission data into durable, versioned datasets. You will work across ingestion, processing, storage, lineage, indexing, and scalable access.

What you will do

• Build reliable ingestion and processing pipelines from sensor and mission systems into curated, versioned, access-controlled datasets.
• Design batch and streaming workflows that handle partial delivery, duplicate or missing events, schema drift, backfills, corruption, and recovery.
• Choose and operate storage formats, partitioning strategies, catalogs, indexes, and query interfaces for high-volume scientific and geospatial data.
• Maintain lineage across source measurements, transformations, datasets, features, and downstream products.
• Build data-quality checks, observability, retention controls, and operational tooling.
• Partner with Agent Infrastructure, research, Signal and Evaluation, Product Intelligence, and Telemetry teams on stable data contracts and scalable access patterns.

Required qualifications

• Experience building production data platforms, distributed data pipelines, storage systems, or large-scale backend infrastructure.
• Strong software engineering skills in Python.
• Experience with databases, schemas, APIs, workflow orchestration, and automated testing.
• Understanding of data-platform failure modes including partial delivery, duplicates, missing events, schema evolution, stale products, corruption, and resource contention.
• Experience operating data systems in cloud or containerized environments and diagnosing performance, reliability, and cost issues.
• Ability to define clear interfaces and communicate tradeoffs across research, product, infrastructure, and operations teams.

Nice to have

• Experience with geospatial, remote-sensing, scientific, image, or other high-dimensional data.
• Experience with AWS, Kubernetes, Docker, Terraform, workflow systems, Postgres, Redis, object storage, or geospatial and vector indexes.
• Experience with streaming, large backfills, data catalogs, metadata systems, access controls, and schema evolution.
• Experience supporting machine-learning training, evaluation, feature, or inference workloads.

Benefits

• Competitive compensation based on experience
• Early-stage equity package
• 100% employer-paid health, dental, and vision coverage
• Opportunity to work on novel sensing, data, and AI systems with real-world deployment paths

Before you apply

• Applicants must be a U.S. citizen or national, a lawful permanent resident (green card holder), or eligible to obtain required authorizations from the U.S. Department of State to comply with U.S. expo

About the company

Matter is building the future of vision AI by pairing a sensor that sees molecular chemistry, temperature, and 3D shape with a Large World Model. The team has delivered technologies to Mars for NASA/JPL and designed advanced sensors for U.S. Defense.