Anduril Industries is a defense technology company focused on transforming military capabilities with advanced technology. The AI Chief Engineering Lead will drive innovations in autonomous vehicle technology by designing algorithms and systems that enhance autonomous capabilities and reduce operator burden.
Responsibilities:
- Develop Advanced Algorithms - Design and implement deep learning and reinforcement learning algorithms to improve sensor perception, prediction, and decision-making for autonomous vehicles
- Apply Agentic Reasoning - Design and implement integrated agents and AI models to solve for end-user autonomous systems workflows
- End-to-End System Integration - Collaborate with cross-functional teams to integrate research prototypes into robust, production-ready systems including simulation environments and real-world platforms
- Research & Experimentation - Conduct research into reinforcement learning strategies and deep architectures, iterate on experimental designs, and evaluate performance using rigorous quantitative metrics
- Data-Driven Innovation - Utilize real-world and synthetic data to enhance model robustness and generalization, leveraging scalable training pipelines on distributed systems
Requirements:
- Sophisticated knowledge of LLM's with an understanding of how they work and how they're applied
- Solid experience with reinforcement learning methods and their application to autonomous systems
- Proven experience of shipping products end to end
- Experience with simulation or real-world validation for autonomous vehicles is highly desirable
- A degree in Computer Science, Robotics, Machine Learning, or a related field, or equivalent practical experience
- Eligible to obtain and maintain an active U.S. Top Secret security clearance
- Travel up to 40+% of time to build, test, and deploy capabilities in the real world
- PhD or Master's degree in Computer Science, Robotics, Machine Learning, or a related field, or equivalent practical experience
- Novel application track record and experience including first author publications, participation in peer reviewed conferences, contribution to open source projects, and demonstrated contribution to the ML and AI community
- Proven experience in deep learning research and development, particularly in generative AI. This includes diffusion models and autoregressive generative models
- Experience in multi-modal sensor data processing (e.g., cameras, LiDAR, radar)
- Familiarity with ML Ops best practices, including model versioning and reproducible research pipelines
- Strong programming skills in Python and familiarity with C/C++ is a plus
- General software engineering experience solving motion planning or related robotics problems