VP of Physical AI & Autonomous Systems

Roboze is redefining how mission-critical parts are made, locally, on demand, and without compromise. Our advanced materials and additive manufacturing platforms are trusted by top Aerospace & Defense organizations around the world. From Europe’s leading primes to major U.S. defense contractors, we help engineers move faster, build stronger, and achieve performance that traditional manufacturing cannot match.

We are not following the old rules of manufacturing. We are rewriting them. And now, from our growing hub in El Segundo, California, we are expanding the team.

Why This Role Matters

Build Roboze’s Physical AI layer, transforming our machines from advanced manufacturing systems into self-optimizing, autonomous production platforms.

This role is responsible for creating

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Autonomous process intelligence inside Roboze machines

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AI-powered factory optimization for customers

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A long-term proprietary data ecosystem across materials, parameters, and qualification workflows

This is not a software AI role. This is AI applied to physics, materials, and real-world production systems.

Reports to: CEO Team Scope: AI/ML, Controls, Data Engineering, Simulation, Embedded System

Strategic Mandate

• Autonomous Process Intelligence (Machine-Level AI)

Make Roboze systems self-learning and self-optimizing.

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Develop AI models that optimize process parameters (temperature, pressure, speed, cooling curves, etc.)

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Real-time defect detection and closed-loop correction using in-situ monitoring and dynamic process parameter adjustment.

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Adaptive parameter tuning for new geometries and materials

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Reduce operator dependency

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Increase first-time-right rate

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Improve gross margins through yield optimization

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Implement assisted algorithms for converting metal part designs into additive composite-ready build files

Goal: Every Roboze machine improves over time. Every Roboze machine autonomously determines how to produce each part. Create Roboze’s proprietary Process Intelligence Operating System (PIOS)

• AI for Factory-Level Optimization (Customer Layer)

Extend intelligence beyond the machine

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Predictive maintenance models

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Production scheduling optimization

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Scrap reduction AI

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Qualification acceleration tools

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AI-based digital twins for simulation before and during printing

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Connect Roboze machines with AGVs and robotic solutions to orchestrate end-to-end automated factory workflows, enabling 24/7 autonomous production.

Goal: Create Roboze’s proprietary Factory Intelligence Operating System (FIOS)

• Build the Roboze Data Ecosystem

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Architect centralized data infrastructure across: Machine sensor data, Material behavior data, Qualification workflows and Failure modes

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Develop proprietary datasets

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Protect and structure process knowledge as a defensible asset

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Collaborate with materials and qualification teams

Goal: Create Roboze’s proprietary Data Intelligence Operating System (DIOS)

What Success Looks Like (24–36 Months)

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Autonomous parameter optimization live on all new systems

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15–25% yield improvement via AI

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Reduced sales cycle via AI-driven qualification tools

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Recurring AI software revenue layer

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Proprietary dataset unmatched in high-performance polymer AM

Key Responsibilities

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Define and execute Roboze’s Physical AI roadmap

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Build and lead cross-functional AI team (ML + Controls + Embedded + Data)

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Partner with Materials, Hardware, and Applications teams

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Drive AI monetization strategy

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Establish long-term architecture (edge + cloud hybrid)

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Oversee AI governance, IP protection, and data strategy

Who You Are

· A strong communicator who enjoys working directly with customers and guiding complex technical discussions.

· A strategic thinker with a hands-on engineering mindset, capable of turning customer challenges into real applications.

· Comfortable working cross-functionally with Business Development, Sales, Marketing, and Production teams.

· Proactive, organized, and autonomous in managing tasks and priorities.

· Experienced in, or motivated to grow within, Aerospace, Defense, or advanced materials environments.

What We Are Looking For

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10+ years in AI/ML applied to physical systems

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Experience in robotics, aerospace systems, semiconductor manufacturing, or advanced industrial automation

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Deep understanding of: Control systems, Sensor fusion, Physics-informed ML and Real-time optimization

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Experience with, Industrial robotics, Semiconductor fabs, Aerospace & Defense fabs, Additive manufacturing and High-performance materials

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Track record of shipping production AI systems (not research only)

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Built AI products with measurable ROI

Technical Stack Exposure (Desired)

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ML frameworks: PyTorch, TensorFlow

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Edge AI deployment

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Reinforcement learning

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Bayesian optimization

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Digital twins / simulation modeling

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Time-series data systems

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Cloud infrastructure (AWS/GCP/Azure)

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Real-time systems integration

Leadership Expectations

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Think like a platform architect, not a feature builder

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Balance speed and scientific rigor

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Translate physics problems into data problems

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Build long-term defensibility, not short-term demos

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Operate with founder-level ownership and speed. Cut through bureaucracy. Question default assumptions and build new standards.

What We Offer

· A performance-driven culture that rewards innovation, speed, and bold thinking,

· Competitive compensation with strong upside for results.

· An environment that values execution over bureaucracy and impact over red tape.

Join the Mission

We are not here for small steps. We are here to reshape how Aerospace & Defense organizations adopt and scale digital manufacturing, challenging traditional models every day.

Roboze’s future is not just machines. It is: Materials + Qualification + Physical AI

This role is responsible for making Roboze

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Harder to copy

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Faster to deploy

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More profitable

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Increasingly autonomous

If you are ready to build the future instead of waiting for it, your mission starts in El Segundo.