Freeform
Principal Machine Learning Researcher (Physical AI)
Los Angeles, CA (On-site) · Principal · Full-time
Sponsorship not specified$200k-$400kDetected 12 days ago
PythonC++Node.jsMachine LearningA/B TestingRoboticsResearchCollaboration
About the role
- This architecture enables continuous generation of petabyte-scale, high-fidelity data capturing the physics of metal printing - from in-situ process signals and machine state to geometry and material outcomes.
- Each factory node contributes to a growing learning system that improves modeling accuracy, control performance, yield, and scalability over time.
- Work includes modeling relationships between process inputs, geometry, and machine state to predict thermal, mechanical, and geometric outcomes during printing, using hybrid physics-ML approaches and multi-modal in-situ data.
Responsibilities
- Develop methods to learn from large-scale, high-dimensional in-situ sensor data collected during printing.
- Develop models that link process parameters, geometry, and machine state to thermal and mechanical outcomes.
- Contribute to the design of closed-loop control and autonomy systems that operate in real time on production hardware.
Requirements
- Experience working with large-scale, noisy, real-world datasets.
Nice to have
- MS or PhD in applied mathematics, physics, robotics, controls, materials science, or a related discipline.
- Experience with image-based or sensor-based inference in industrial or scientific settings.
- Familiarity with computational geometry or geometric modeling.
- Comfort working across theory, experimentation, and deployment in tightly coupled systems.
- Ability to reason from first principles and translate theory into working models and systems.
- Based in Hawthorne, our vertically integrated facility brings technology development, R&D, and production together under one roof.
- We operate at the center of LA's deep tech ecosystem, surrounded by some of the most ambitious hardware innovation happening anywhere in the country.
- Traditional and Roth 401(k)
Compensation
- Our intent is to offer a salary that is commensurate for the company's current stage of development and allows the employee to grow and develop within a role. <span class="EOP SCXW113124793 BCX0" data-ccp-pr
Benefits
- We have an inclusive and diverse culture that values collaboration, learning, and making deliberate data-driven decisions.
- Significant stock option packages
- 100% employer-paid Medical, Dental, and Vision insurance (premium PPO and HMO options)
- Life insurance
- Paid vacation, sick leave, and company holidays
- Generous Paid Parental Leave and extended transition back to work for the birthing parent
- Casual dress, flexible work hours, and regular catered team building events
- Design and develop machine learning models for complex, multi-physics manufacturing processes.
- Lead the formulation of learning-based models used for prediction and control in production-scale metal additive manufacturing systems.
- Design unsupervised and self-supervised learning techniques to correlate process signals with part quality, geometry, and performance.
- Develop learning-based approaches for machine health monitoring, anomaly detection, and system diagnostics.
- Guide the integration of machine learning models into production software and manufacturing workflows.
- Develop hybrid modeling approaches that combine first-principles physics with data-driven learning.
Company info
- We offer a unique opportunity to be an early and integral member of a rapidly growing company that is scaling a world-changing technology.
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