Walaris Tech Stack

AI-powered autonomous threat detection for defense and critical infrastructure

Defense and Space Manufacturing Atlanta, Georgia 51–200 employees Privately Held

Walaris builds AI-driven autonomous systems for counter-UAS and perimeter surveillance, with a tech stack centered on MLOps (Kubeflow, MLflow, Airflow) and computer vision (PyTorch, TensorFlow, Deepstream). The engineering-heavy hiring mix—6 of 7 active roles in engineering—paired with active projects in MLOps pipeline development and edge sensor signal processing suggests the company is scaling internal ML infrastructure to support real-time threat detection at the edge. Concurrent work on ISO 9001 certification and military-systems integration indicates a scaling organization bridging software agility with defense-grade compliance.

Tech Stack 36 technologies

Core StackKubeflow MLflow Apache Airflow Docker Kubernetes GitLab CI/CD Python AWS PyTorch TensorFlow scikit-learn C++ Flask GitLab Jenkins Rust JavaScript TypeScript React DataRobot Bash Azure GCP Keras GStreamer Deepstream ZeroMQ TCP/IP UDP HTML5+6 more

What Walaris Is Building

◆Challenges

Achieving iso 9001 certification
Compliance with defense regulations
Scalable mlops pipelines
Real-time situational awareness
Data engineering pipelines
Real-time responsiveness in mission-critical environments
Optimizing procurement processes

▲Active Projects

Integration into military systems
Mlops pipeline development
Back-end architecture improvements
Implementing qms for iso 9001 certification
Supporting external audits
Ci/cd pipeline orchestration
Edge sensor signal processing for drone detection
Command-and-control (c2) systems
Real-time user interfaces for ai/ml-driven edge processing systems
Visualization tools for sensor data

Hiring Activity

Accelerating7 roles · 7 in 30d

Department

Engineering

Ops

Seniority

Mid

Manager

Senior

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About Walaris

Walaris develops software-defined autonomous situational awareness systems for government, marine, and critical infrastructure protection customers worldwide. The company licenses proprietary AI and computer vision software alongside integration and engineering services. Its product surface spans counter-UAS threat detection, perimeter surveillance, and command-and-control systems. Core technical stack emphasizes ML model development and deployment (Kubeflow, MLflow, DataRobot), containerization (Docker, Kubernetes), and real-time video processing (GStreamer, Deepstream). The organization is pursuing ISO 9001 certification while integrating systems into military platforms.

HeadquartersAtlanta, Georgia

Company Size51–200 employees

Hiring MarketsGermany

Frequently Asked Questions

What tech stack does Walaris use?

Walaris uses Kubeflow, MLflow, and Airflow for MLOps; PyTorch and TensorFlow for model development; Docker and Kubernetes for deployment; and GStreamer and Deepstream for real-time video processing. AWS, Azure, and GCP provide cloud infrastructure.

What is Walaris working on?

Active projects include MLOps pipeline development, edge sensor signal processing for drone detection, command-and-control systems, real-time AI/ML-driven user interfaces, ISO 9001 certification implementation, and integration into military systems.

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How this profile is built

Walaris's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.