Lead AI/ML Engineer – Build the Brain Behind Autonomous Defense Systems!

Austin, TX | Hybrid

Opportunity Summary

A seed-stage robotics startup is developing intelligent autonomous systems designed to operate in demanding real-world defense environments. These platforms rely on advanced perception, learning, and decision-making to detect and respond to small aerial threats in real time. The team is lean, highly technical, and moving quickly through design, testing, and field deployment. As the Lead AI/ML Engineer, you will own the machine learning intelligence that powers these autonomous systems. You will architect, train, optimize, and deploy real-time inference models that must run reliably under strict compute and power constraints at the edge. This role is perfect for an engineer who enjoys working close to both the hardware and mission, who can design ML systems from first principles, and who thrives in an environment where models are directly tied to real-world performance and safety.

About Us

We are a funded deep-tech startup building autonomous robotic platforms that deliver mission-critical decision-making in dynamic environments. Our work combines robotics, sensing, edge computing, and advanced AI to create highly capable autonomous systems used across national security applications. With a small expert team and modern lab resources, we are focused on rapidly iterating from research to deployed capability.

Job Duties

• Design, train, and optimize neural network architectures for fast classification and tracking in cluttered environments

• Develop and refine sensor fusion pipelines to combine multisource data across RF, optical, radar, and acoustic inputs

• Lead the machine learning deployment lifecycle for edge environments, including optimization, packaging, and monitoring

• Build anomaly detection and adaptive learning models that can identify emerging or unseen threat signatures

• Work closely with robotics and controls engineers to ensure model outputs integrate cleanly into real-time guidance and decision systems

• Contribute to modeling strategy, experimentation frameworks, and architecture direction across the AI stack

Qualifications

• Strong Python experience and deep familiarity with modern ML frameworks such as PyTorch or TensorFlow

• 3+ years building and deploying machine learning models for classification, perception, or sensing applications

• Experience working with sensor fusion or multimodal data

• Demonstrated ability to optimize models for resource-constrained or edge-compute environments

• Strong fundamentals across linear algebra, probability, and optimization relevant to ML system design

• Ability to work hands-on across the entire ML lifecycle from data to fielded performance

Preferred Experience

• Experience with autonomous systems, defense technology, robotics, UAVs, or aerospace platforms

• Contributions to applied ML systems operating in the field rather than purely research environments

• Familiarity with edge inference strategies, embedded ML, or low-latency system design

• Prior experience in early-stage startups or small technical teams

• Existing or attainable security clearance

• Passion for hardware, robotics builds, or personal engineering projects

Why Join Us

• Direct ownership over the AI systems that define real-world mission performance

• Small, highly technical team with rapid decision cycles and meaningful responsibility

• Opportunity to shape architecture, roadmap, and product capability from the early stages

• Hands-on environment working with modern lab tools, robotic platforms, and test hardware

Compensation Details

$140,000 - $200,000

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