Principal Machine Learning Researcher (Physical AI)

PRINCIPAL MACHINE LEARNING RESEARCHER (PHYSICAL AI)

Freeform builds AI-native manufacturing systems that unify software, hardware,

and physics to produce industrial-scale parts at the speed of human ideation. By

treating manufacturing as a single integrated system, we unlock a new era of

innovation where complex hardware is designed, built, and scaled without limits.

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.

Freeform is hiring a Principal Machine Learning Researcher to lead the

development of advanced learning and control problems in a production-scale,

AI-native metal manufacturing system. The role focuses on developing machine

learning methods that integrate large-scale physical data with physics-based

simulation and embedding these models into closed-loop control and autonomy

frameworks. 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.

Research is validated against physical outcomes and deployed into production

systems, where improvements directly impact stability, yield, throughput, and

capability across an expanding fleet of manufacturing nodes. Your work will have

a direct and meaningful impact on how frontier technologies are designed and

produced at scale.

Responsibilities

• * Design and develop machine learning models for complex, multi-physics
• manufacturing processes.
• * Develop hybrid modeling approaches that combine first-principles physics with
• data-driven learning.
• * Lead the formulation of learning-based models used for prediction and control
• in production-scale metal additive manufacturing systems.
• * Develop methods to learn from large-scale, high-dimensional in-situ sensor
• data collected during printing.
• * Design unsupervised and self-supervised learning techniques to correlate
• process signals with part quality, geometry, and performance.
• * Develop models that link process parameters, geometry, and machine state to
• thermal and mechanical outcomes.
• * Integrate learned models with physics-based simulation and digital twin
• frameworks.
• * Contribute to the design of closed-loop control and autonomy systems
• that operate in real time on production hardware.
• * 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.
• * Help define research direction and technical standards for machine learning
• applied to physical systems within the organization.
• Basic

Qualifications

• * 5+ years of experience in machine learning, applied research, or related
• technical fields or a PhD in machine learning, applied mathematics, physics,
• robotics, controls, or a closely related discipline.
• * Strong foundations in machine learning applied to physical systems, modeling,
• or control.
• * Proficiency in Python and at least one systems-level programming language
• (C/C++ preferred).
• * 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 hybrid physics–ML models, digital twins, or
• simulation-in-the-loop learning.
• * Background in autonomy, robotics, model predictive control, or reinforcement
• learning for physical systems.
• * 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.
• Location:
• * 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.
• * Our fast-paced, cross-functional environment is built on close collaboration,
• and as such, this role requires full-time onsite presence (five days a week),
• with very limited exceptions.
• What We Offer:
• * We have an inclusive and diverse culture that values collaboration, learning,
• and making deliberate data-driven decisions.
• * We offer a unique opportunity to be an early and integral member of a rapidly
• growing company that is scaling a world-changing technology.
• * Benefits
• * Significant stock option packages
• * 100% employer-paid Medical, Dental, and Vision insurance (premium PPO and
• HMO options)
• * Life insurance
• * Traditional and Roth 401(k)
• * Relocation assistance provided
• * Paid vacation, sick leave, and company holidays
• * Generous Paid Parental Leave and extended transition back to work for the
• birthing parent
• * Free daily catered lunch and dinner, and fully stocked kitchenette
• * Casual dress, flexible work hours, and regular catered team building events
• * Compensation
• * As a growing company, the salary range is intentionally wide as we
• determine the most appropriate package for each individual taking into
• consideration years of experience, educational background, and unique
• skills and abilities as demonstrated throughout the interview process. 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.
• * In addition to the significant stock option package, the estimated salary
• range for this role is $200,000-$400,000. However is this a unique position
• with outsized impact for the right game-changing hire, so we will consider
• compensation outside of this range on a case-by-case basis.
• * Freeform is an Equal Opportunity Employer that values diversity; employment
• with Freeform is governed on the basis of merit, competence and
• qualifications and will not be influenced in any manner by race, color,
• religion, gender, national origin/ethnicity, veteran status, disability
• status, age, sexual orientation, gender identity, marital status, mental or
• physical disability or any other legally protected status.