Primordial Labs
Primordial Labs is developing an advanced human-machine interface called Anura, aimed at enhancing human collaboration with uncrewed systems (UxS). Anura allows operators, particularly warfighters, to task robots using natural language, treating them like human teammates rather than mere tools. The company focuses on revolutionizing the communication mechanism to improve the adoption of autonomous systems by integrating Natural Language Understanding with platform-agnostic autonomy. Anura translates verbal, mission-type orders into complex autonomous actions for various systems, enabling more intuitive and effective battlefield management and command control of uncrewed systems.
Human-Centric AI System Design • Autonomous Systems C2 • Natural Language Interfaces • Automated Mission Planning Support • Platform-Independent AI Integration
Machine Learning Engineer - Deep Reinforcement Learning
October 20, 2024
Primordial Labs
Primordial Labs is developing an advanced human-machine interface called Anura, aimed at enhancing human collaboration with uncrewed systems (UxS). Anura allows operators, particularly warfighters, to task robots using natural language, treating them like human teammates rather than mere tools. The company focuses on revolutionizing the communication mechanism to improve the adoption of autonomous systems by integrating Natural Language Understanding with platform-agnostic autonomy. Anura translates verbal, mission-type orders into complex autonomous actions for various systems, enabling more intuitive and effective battlefield management and command control of uncrewed systems.
Human-Centric AI System Design • Autonomous Systems C2 • Natural Language Interfaces • Automated Mission Planning Support • Platform-Independent AI Integration
📋 Description
• Developing policies for low to high-level task assignments. • Transitioning policies to physical unmanned vehicles. • Incorporating new aircraft/sensor models into simulation frameworks.
🎯 Requirements
• Proven experience in machine learning and reinforcement learning. • Expertise in closing the sim2real gap. • Knowledge of sparse rewards and credit assignment over long time horizons. • Experience in offline learning and options learning. • Familiarity with unsupervised exploration techniques. • Gym development experience, especially around complex DoD wargaming.
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