Data & ML Infrastructure Engineer (AI)

Location: Remote; U.S. citizenship and the ability to obtain and maintain a U.S. Government security clearance are required

Salary: $150,000–$185,000 per year, plus equity and bonus opportunities

Company

hirify.global develops software-defined hardware and collaborative autonomy systems for defense and commercial applications across sea, air, and land.

What you will do

• Build and maintain infrastructure for video, imagery, telemetry, sensor data, autonomy logs, mission data, and field-test data.
• Own ingestion, storage, indexing, metadata, access patterns, and lifecycle management for the internal data lake.
• Develop scalable pipelines and reproducible workflows for ML training, evaluation, debugging, regression testing, and benchmarking.
• Build tools for data search, filtering, tagging, retrieval, replay, visualization, and analysis.
• Establish dataset quality, lineage, versioning, monitoring, observability, and validation standards.
• Partner with Autonomy, Perception, Software, Simulation, Field Operations, and Program teams to turn engineering requirements into scalable data capabilities.

Requirements

• Bachelor’s degree in computer science, data science, machine learning, electrical engineering, computer engineering, robotics, applied mathematics, or a related technical field.
• 3+ years of experience in data engineering, ML infrastructure, data platforms, backend systems, MLOps, or related engineering roles.
• Experience operating production pipelines for large-scale structured, semi-structured, or unstructured datasets, including video, imagery, telemetry, sensor data, or logs.
• Strong programming skills in Python and SQL, with experience in cloud storage, object stores, data lakes, databases, distributed processing, or modern data platforms.
• Experience with dataset versioning, metadata management, data lineage, access controls, reproducibility, testing, reliability, and observability.
• U.S. citizenship and ability to obtain and maintain a U.S. Government security clearance.

Nice to have

• Experience with ML infrastructure, MLOps, training pipelines, experiment tracking, model evaluation, or model registries.
• Experience with S3-compatible storage, PostgreSQL, Spark, Ray, Airflow, Dagster, Kubernetes, Docker, or Kafka.
• Experience with autonomous-system datasets, computer vision annotation, sensor synchronization, timestamp alignment, or multimodal dataset construction.
• Experience with security, auditability, and data-handling requirements in government, defense, robotics, aerospace, or dual-use technology programs.
• Active or prior security clearance.

Culture & Benefits

• Employer-paid health, dental, and vision insurance for employees and families.
• Employer-paid life insurance and access to a 401(k) program with matching.
• Unlimited paid time off with an enforced two-week minimum.
• Equity package, work-from-home office stipend, Global Entry, and monthly health and wellness stipend.
• Sixteen weeks of paid parental leave.
• Mission-driven environment focused on innovation, integrity, ownership, and advanced defense technology.