Spear AI builds machine learning systems for U.S. national security and defense customers, with a tech stack spanning PyTorch, TensorFlow, and cloud infrastructure (AWS, Azure, GCP, AWS GovCloud). The hiring profile—9 of 10 open roles in engineering, mostly senior-level—reflects active development across real-time and offline data pipelines, acoustic ML, and maritime domain awareness systems. Pain points around air-gapped deployment, CMMC compliance, and firmware CI/CD indicate customers operating in highly regulated, disconnected environments.
Tech Stack 40 technologies
Core StackPyTorch TensorFlow scikit-learn Python AWS JavaScript Java Go Apache Spark Kafka Apache Airflow Dagster PostgreSQL Apache Iceberg Vanta Pulumi Docker Kubernetes Fairlearn Azure GCP AWS GovCloud Parquet WebGPU MQTT Redpanda Kandji 1Password C/C++ Protocol Buffers+10 more
What Spear AI Is Building
◆Challenges
- Ensuring cmmc compliance
- Deploying to air-gapped environments
- Transitioning away from ros2
- Maintaining cloud integration
- Field deployment logistics
- Managing secrets and configuration
- Lack of ci/cd pipeline for embedded firmware
- Improving provisioning and configuration systems
- Integration between cloud and hardware systems
- Scaling design engineering
▲Active Projects
- Real-time data feeds
- Offline data pipelines
- Next-generation data management and ai platform for maritime domain awareness
- Machine learning model integration
- Ai-enabled acoustic buoy software development
- Cross-platform dsp library development
- Cloud api integration
- Cloud architecture design and implementation
- Ci/cd and devsecops pipeline development
- Unmanned maritime sensor systems
Hiring Activity
10 roles · 9 in 30d
Department
Seniority
Company intelligence
