Data/ML Infrastructure Engineer

Responsibilities

• Design, build, and operate scalable data and ML infrastructure on AWS, including workloads running on Kubernetes
• Build and maintain systems for ingestion, processing, storage, and serving with guarantees around data quality and operational safety
• Partner with research to support perception model training and evaluation workflows
• Build platform primitives for observability, data versioning, lineage, and reproducibility
• Partner with product engineering to ensure data- and model-derived insights are accessible through low-latency serving interfaces
• Design systems for efficient access patterns including search, indexing, and large-scale querying
• Identify and address bottlenecks in throughput, cost, and operational complexity

Requirements

• Meaningful experience building production data infrastructure, ML infrastructure, or distributed systems
• Strong programming skills in Python and SQL
• Experience building and operating systems on AWS
• Familiarity with Kubernetes, Docker, and Terraform
• Experience with production storage and serving systems such as Postgres and Redis
• Familiarity with data and ML workflow tooling such as Metaflow
• Strong instincts for observability, testing, and operational excellence
• Must be a U.S. citizen, national, lawful permanent resident, or eligible for Department of State authorization

Preferred Qualifications

• Experience supporting ML training, evaluation, batch inference, or model deployment in production
• Familiarity with large-scale data patterns including streaming, backfills, and schema evolution
• Experience building internal platform primitives like data versioning, lineage, or experiment tracking
• Exposure to perception, multimodal, or geospatial systems

Benefits

• Competitive compensation based on experience
• Early-stage equity package
• 100% employer-paid health, dental, and vision coverage

About the Company

Matter works on novel sensing, data, and AI systems with real-world deployment paths across drone, aerial, and orbital platforms.