--- title: 'Principal Machine Learning Researcher (Physical AI) at Freeform' canonical: 'https://feeny.ai/job/principal-machine-learning-researcher-physical-ai-freeform-los-angeles-663pzmgqpzjm' type: 'job' last_seen: '2026-09-12' --- # Principal Machine Learning Researcher (Physical AI) at Freeform - **Company:** Freeform - **Location:** Los Angeles, CA - **Work type:** onsite - **Posted:** 2026-09-08 - **Last confirmed live:** 2026-09-12 - **Apply:** https://job-boards.greenhouse.io/freeformfuturecorp/jobs/7989254003 ## Job description ## 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: - PhD in computer science, applied mathematics, physics, robotics, controls, or a closely related discipline. - 5+ years of experience in machine learning, applied research, or related technical field. - 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: - 10+ years of industry experience - Experience with hybrid physics–ML models, digital twins, or simulation-in-the-loop learning. - Background in autonomy, robotics, model predictive control, optimal 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-$500,000. However this is a uniquely impactful role and we are open to discussing compensation packages outside of this range for the right person. - 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. ## About Freeform ## Company Overview - **One-liner**: Freeform builds the world’s first AI-native manufacturing system – autonomous factories that use advanced sensing, compute, and machine learning to 3D-print industrial-grade metal parts at unprecedented speed and scale. - **Entity Type**: Private (Series B, raised $67M in Feb 2026) - **Headquarters**: Hawthorne, California, USA - **Founded**: 2019 - **Founders**: Erik Palitsch (CEO), Thomas J. Ronacher (President & Co-Founder) ## Core Business - **Primary industry/industries**: Industrial Automation, Additive Manufacturing (Metal 3D Printing), Physical AI - **Target customers**: B2B, primarily serving mission-critical industries: Aerospace & Defense, Aviation, Automotive, Advanced Energy, Consumer Electronics, Robotics, and Motor Sports. - **Mission or purpose statement**: “To radically change the way things are made” and “unlock advanced manufacturing for every industry” by treating manufacturing as a single, integrated AI-native system. ## Products & Services For each major offering: - **AI-Native Manufacturing System**: A fully integrated, software-defined network of autonomous factories. This system uses proprietary compute, sensors, controls, and ML to sense, learn, predict, and control metal formation in real-time. It unifies hardware and software to produce industrial-scale parts from prototype to full production, all under one roof. - **Physical AI Stack**: The company built its own technology stack (compute, sensors, controls, software) to enable a new method of metal 3D printing that is faster, more predictable, and cost-effective than traditional methods. ## Market Standing - **Valuation/Market Cap**: Not publicly disclosed - **Key Metric**: Annual Revenue: $4.5M (LinkedIn estimate); Total Funding: $126M - **Notable Investors/Partners**: NVIDIA (NVentures), AE Industrial Ventures (AE Ventures), Two Sigma Ventures, Founders Fund, Threshold Ventures, 8VC, Linse Capital, Valor. - **Growth Signals**: - Raised $67M Series B in February 2026 to scale up laser AI manufacturing. - Named to Fast Company’s “World’s Most Innovative Companies of 2026.” - 48 active job postings as of mid-2026, with year-over-year hiring growth of +81.5%. - Headcount growth of 9.4% year-over-year (approximately 50 employees). - Key hires from SpaceX, Tesla, Apple, Google, Velo3D. ## Competitive Advantages - **First-principles technology**: The company built all technology from scratch (compute, sensors, controls, ML stack) because the necessary tech didn't exist. This creates a deep technical moat. - **AI-native, not AI-applied**: Their system is designed from the ground up to be autonomous, learning, and predictive, unlike traditional manufacturing methods that apply AI as an afterthought. - **Proven leadership**: Founded and led by ex-SpaceX engineers (Erik Palitsch was Principal Architect of the Starship Vehicle and led the Merlin & Raptor engine programs) and a Chief Scientific Officer with deep experience in additive manufacturing (Tasso Lappas, former CTO at Velo3D). - **Speed and scale**: Promises the ability to go from prototype to full-scale production faster than any competitor, enabling a "death of slow speeds and unpredictable systems." ## Strategic Focus - **Scale up operations**: The primary focus of the $67M Series B is to scale the technology and expand production capacity. - **Industry expansion**: Targeting a wide range of industries including aerospace, defense, automotive, energy, and consumer electronics. - **Talent acquisition**: Aggressively hiring top-tier cross-disciplinary talent (MechE, Electrical, Software, ML/AI, Process, and Engineering leadership) to build out the team. - **Product innovation**: Continuing to push the boundaries of speed, quality, and scale in metal additive manufacturing. ## Why Work Here - **Culture**: Described as a team of "first-principles thinkers" with "low ego" and a "healthy sense of humor." The company emphasizes working on "hard problems" and is driven by a mission to fundamentally change manufacturing. - **Working policy**: Fully on-site in Los Angeles, CA (Hawthorne). This is a shop-floor and lab-heavy environment, ideal for those who want to be hands-on with hardware. - **Compensation & Equity**: Offers competitive compensation and pre-IPO shares, meaning all employees are shareholders in the company’s success. - **Notable Perks & Engineering Culture**: Opportunity to work with some of the most advanced manufacturing technology in the world (lasers, robotics, ML). The environment is described as high-trust, high-impact, and cross-disciplinary. The company encourages applications even if there is no exact role listed, signaling a flexible and growth-oriented culture. - **Talent density**: The team includes top talent from SpaceX, Apple, Google, Tesla, Velo3D, and other leading tech and manufacturing companies. ## Sources 1. [freeform.co](https://freeform.co/) 2. [Freeform Careers](https://freeform.co/careers) 3. [Freeform Company Page](https://freeform.co/company) 4. [Freeform Greenhouse Job Board](https://job-boards.greenhouse.io/freeformfuturecorp) 5. [LinkedIn - Freeform](https://www.linkedin.com/company/freeformfuture) 6. [TechCrunch - $67M Series B](https://techcrunch.com/2026/02/19/freeform-raises-67m-series-b-to-scale-up-laser-ai-manufacturing/) 7. [TechCrunch - $14M Venture Round](https://techcrunch.com/2024/10/22/ex-spacex-engineers-land-14m-to-scale-new-method-for-3d-printing-metal/) ## Other roles at Freeform - [Electrical Engineering Intern (Spring 2027)](https://feeny.ai/job/electrical-engineering-intern-spring-2027-freeform-los-angeles-0806bphqm9rg) — Los Angeles, CA - [Senior Factory Infrastructure Engineer](https://feeny.ai/job/senior-factory-infrastructure-engineer-freeform-los-angeles-m0pv1y34aqqz) — Los Angeles, CA - [Factory Infrastructure Engineer](https://feeny.ai/job/factory-infrastructure-engineer-freeform-los-angeles-62ec1ncja35w) — Los Angeles, CA - [Additive Engineering Intern (Summer 2027)](https://feeny.ai/job/additive-engineering-intern-summer-2027-freeform-los-angeles-1jkg1yg9wb5k) — Los Angeles, CA - [Mechanical Engineering Intern (Spring 2027)](https://feeny.ai/job/mechanical-engineering-intern-spring-2027-freeform-los-angeles-vyt1gep498wt) — Los Angeles, CA - [Electrical Engineering Intern (Summer 2027)](https://feeny.ai/job/electrical-engineering-intern-summer-2027-freeform-los-angeles-yq6a82we64ds) — Los Angeles, CA - [Manufacturing Engineering Intern (Summer 2027)](https://feeny.ai/job/manufacturing-engineering-intern-summer-2027-freeform-los-angeles-hyrnk42qmhyd) — Los Angeles, CA - [Process Engineering Intern (Summer 2027)](https://feeny.ai/job/process-engineering-intern-summer-2027-freeform-los-angeles-ahm5ck5w13a5) — Los Angeles, CA - [Electrical Engineer (New Grad Summer 2027)](https://feeny.ai/job/electrical-engineer-new-grad-summer-2027-freeform-los-angeles-eeppz69v0gpa) — Los Angeles, CA - [Manufacturing Engineer (New Grad Summer 2027)](https://feeny.ai/job/manufacturing-engineer-new-grad-summer-2027-freeform-los-angeles-k0jdheqkmmvc) — Los Angeles, CA