Principal Simulation Engineer

Freeform

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.

PhysicsX

ABOUT US PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive. WHO WE'RE LOOKING FOR As a Principal Machine Learning Engineer in Delivery, you are an experienced problem solver and technical leader who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, lead technical initiatives, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used. You’ve shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools and make pragmatic product decisions that set Delivery up for success. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products. With at least 5 years industry experience (post Masters or PhD) in a commercial, non-research environment, you're ready to not only execute but also lead and mentor others. You're truly excited about taking ownership of complex work streams and guiding teams to success, while continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers. THIS ROLE  As a Principal MLE, you'll work closely with our Data Scientists, Simulation Engineers, and customers to understand and define the engineering and physics challenges we are solving. You will iterate with customers and use your influence to drive decisions around reliable deployment with measurable outcomes. You'll: * Own the deployment of ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data, time‑series forecasting, anomaly detection, optimization & control) to customer production environments. * Communicate results and trade‑offs to senior stakeholders; steer roadmaps and influence product direction with evidence. * Lead scoping and architecture design for data/ML systems; define success metrics, delivery plans and quality bars. * Excel at building robust and scalable ML systems, training and inference pipelines and APIs, running both on cloud and on-prem environments. The tech stack you will use for this includes: Python, PyTorch, Pandas, fastAPI, Scipy, Kubeflow, among others. * Mentor and develop engineers and data scientists; provide technical direction and clear, calm decision‑making under pressure. * Travel to customer sites in North America, Europe, Asia, Oceania, for an average of 3-4 weeks per quarter, where you'll collaborate closely with customers to build solutions on-site. * Own the scoping of new projects and work-streams with existing customers and taking part in bringing new customers to PhysicsX. As a senior member of the team, you’ll significantly influence our technical direction and will be involved in shaping future solutions and products, while developing your skills as a technical leader.   OUR DELIVERY TEAMS DRIVE INNOVATION TO TURN AI MODELS INTO PRACTICAL SOLUTIONS - READ OUR BLOG TO LEARN MORE ABOUT HOW YOU’LL CONTRIBUTE TO THIS EXCITING JOURNEY!    We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.    We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.

PhysicsX

ABOUT US PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive. WHO WE'RE LOOKING FOR As a Principal Data Scientist (Algorithm Engineer) in Delivery, you are an experienced problem solver and technical leader who is passionate about building practical solutions that enable customers to make better engineering decisions. You are someone who can grasp advanced engineering concepts across multiple industries, lead technical initiatives, and excel at working directly with customers (and often side-by-side with them on-site) to embeds cutting edge AI models into tools that are useful and used. You've consistently tackled difficult problems that require strong foundations in data driven modelling and deep learning techniques, with extensive hands-on experience in probabilistic methods and predictive modelling. Your expertise in python, along with advanced proficiency in libraries like NumPy, SciPy, Pandas, TensorFlow and PyTorch, is essential, with proven ability to architect and deploy scalable, production-ready models and data pipelines. With industry experience (post Masters of PhD) in a commercial, you're ready to not only execute but also lead and mentor others. You're truly excited about growing both your technical expertise and leadership skills, naturally taking ownership of complex data science work streams and guiding teams to success. You continuously improve the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers. THIS ROLE In this role, you'll work closely with our Simulation Engineers, Machine Learning Engineers, and customers to understand and define the engineering and physics challenges we are solving, while providing technical leadership to your team. You'll build the foundations for successful, impactful solutions by: * Leading pre-processing and analysis of complex data to prepare it for use in predictive modelling, establishing best practices and methodologies for your team. * Architecting and developing innovative deep learning models in combination with state-of-the-art optimisation methods to predict and control the behaviour of physical systems. * Taking full responsibility for the quality, accuracy and impact of your work and the work of your team. * Designing, building, and testing data pipelines that are reliable, scalable, and robustlyeasily deployable in production environments. * Leading cross-functional collaboration with simulation engineers to ensure seamless integration of data science models with simulations. * Driving internal R&D and product development, helping to refine models and identify new areas of application. * Mentoring junior team members and providing technical guidance to help them grow. * Leading open communication and presentations with both technical teams and customers, helping onboard users and co-develop with customers. * Representing PhysicsX as a technical authority when traveling to customer sites in North America, Europe, Asia, Oceania, an average of 2-3 weeks per quarter, where you'll collaborate closely with customers to build solutions on site. As a senior member of the team, you'll have significant influence on our technical direction and the opportunity to shape future solutions and products, while developing your skills as a technical leader. OUR DELIVERY TEAMS DRIVE INNOVATION TO TURN AI MODELS INTO PRACTICAL SOLUTIONS - READ OUR BLOG TO LEARN MORE ABOUT HOW YOU’LL CONTRIBUTE TO THIS EXCITING JOURNEY!   We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.    We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.