Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st…
The Robotics Software Engineer joins Anduril's Command and Control Software team to build real-time path planning, trajectory optimization, and multi-agent coordination for autonomous unmanned systems. The role uses C/C++ and Rust, simulation, and concurrent software integrated into field-deployed defense C2 platforms.
Builds, scales, and optimizes Anduril's machine learning platform and MLOps tooling for autonomous systems, including training, evaluating, and serving AI models (LLMs, computer vision, RL) across cloud and air-gapped edge environments. Uses Python/Go/C++, Docker/Kubernetes, and distributed training frameworks.
Designs and deploys path-planning and trajectory-optimization algorithms for real-time command-and-control (C2) systems that orchestrate fleets of unmanned platforms. Day-to-day work uses C/C++, Python, and Matlab to build graph-based and sampling-based planners, multi-agent coordination, and decision-making for defense missions.
Designs and deploys real-time path planning and route optimization algorithms for command-and-control systems that orchestrate fleets of unmanned systems. Uses C/C++ and/or Rust with graph search, sampling-based planners, trajectory optimization, and concurrent software for autonomous ground, air, and maritime platforms.
Senior Software Engineer on the Battlespace Awareness Command and Control team at Anduril, building computationally efficient high-fidelity models of vehicle dynamics, interceptor performance, and weapon system effectiveness to support real-time threat prediction and battle management decisions. Core technologies include Python, MATLAB, GNC, trajectory prediction, state estimation, path planning,
Backend software engineer who owns Anduril's internal LLM agent framework, building platform capabilities so teams can develop, evaluate, and deploy reliable LLM agents in mission-critical defense environments. Core technologies include agent orchestration, model post-training, evaluation tooling, and cloud infrastructure.
Software Engineer developing real-time path planning, trajectory optimization, and autonomous mission execution for command and control systems in defense technology, using C/C++ and Rust to build algorithms for multi-agent coordination and vehicle autonomy.
Software Engineer focusing on guidance, navigation, and control (GNC) modeling for defense command-and-control systems. Builds high-fidelity physics simulations, trajectory prediction, and resource allocation models using Python, MATLAB, and C/C++ to support real-time threat prediction and autonomous mission execution.
Designs, builds, and scales Anduril's machine learning platform for autonomous defense systems, creating MLOps tooling, distributed training and model-serving infrastructure, and ETL pipelines for terabytes of multi-modal sensor data across cloud and air-gapped tactical edge environments, while leading and mentoring the infrastructure team.
Designs and deploys machine learning models and algorithms for missile defense systems, including track fusion, threat assignment, and sensor fusion, using Python/C++ and ML frameworks like PyTorch or TensorFlow on Anduril's Space Ground Systems Engineering team.
Builds and manages compute infrastructure for scalable machine learning operations at defense tech company Anduril, using Docker, Kubernetes, CI/CD, and Infrastructure-as-Code across cloud, on-premise, and hybrid deployments while collaborating with customers and researchers to productize ML workloads.
Builds, evaluates, and deploys AI systems and applications to solve internal engineering and business problems at SpaceX, using Python, ML frameworks like PyTorch, Docker, and Kubernetes to move prototypes through deployment.
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