Freeform · 11 hours ago
Principal Machine Learning Researcher
Freeform builds AI-native manufacturing systems that integrate software, hardware, and physics for industrial-scale production. They are seeking a Principal Machine Learning Researcher to lead the development of advanced learning and control problems in metal manufacturing, focusing on integrating machine learning methods with large-scale physical data and physics-based simulations.
3D TechnologyElectronicsIndustrial AutomationMachinery ManufacturingRobotics
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
Qualification
Required
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
Preferred
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
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
Company
Freeform
Freeform is a 3D printing company offering metal 3D printing solutions for manufacturing companies.
Funding
Current Stage
Early StageTotal Funding
$117.88MKey Investors
Two Sigma Ventures
2026-01-07Series Unknown· $58.88M
2024-10-22Series Unknown· $14M
2023-02-01Series Unknown· $45M
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