Gen AI Research Scientist - Edge & Multi-Agent Autonomy

Anduril Industries; Washington (District of Columbia); On-site; USD 220,000 - 292,000; Full time

Benefits offered by this job

Equity grants

Top-tier benefits

Job summary

Anduril Industries is seeking an AI Research Scientist to lead the design, fine-tuning, and deployment of next-generation generative AI, LLMs, and agentic systems powering its air-dominance platforms. This highly applied role blends 60% applied research with 40% hands-on coding, focusing on running state-of-the-art models on power- and compute-constrained edge hardware.

You will set technical direction, define data collection across test sites and simulations, and influence multi-agent autonomy

Qualifications

• Strong production-level coding skills in Python and deep learning frameworks (PyTorch, JAX).
• Experience training, fine-tuning, and evaluating LLMs, Generative AI, or multimodal models.
• Background in Computer Vision, NLP, Robotics, or Speech with 2+ years in generative models and transformer architectures.
• Degree in CS/ML/Robotics/Physics/Math and eligibility for a U.S. Top Secret security clearance.

Responsibilities

• Develop, pre-train, and fine-tune in-house LLMs and multimodal foundation models.
• Architect and optimize models to run on edge compute and power-constrained hardware.
• Design robust agentic architectures and multi-agent planning loops for multi-domain missions.
• Collaborate with CV, perception, and motion planning teams across modalities (camera, radar, telemetry, text).
• Define data collection strategies across physical assets and simulations; build scalable evaluation frameworks.

Skills

Python

Deep learning

LLM training

Transformer models

Edge deployment

Model evaluation

Education

BS/MS/PhD in CS/ML/Robotics/Physics/Math

Tools

PyTorch

JAX

DeepSpeed

Megatron-LM

LangChain

LlamaIndex

Job description

Anduril Industries is seeking an AI Research Scientist to lead the design, fine-tuning, and deployment of next-generation generative AI, LLMs, and agentic systems powering its air-dominance platforms. This highly applied role blends 60% applied research with 40% hands-on coding, focusing on running state-of-the-art models on power- and compute-constrained edge hardware.

You will set technical direction, define data collection across test sites and simulations, and influence multi-agent autonomy