ARTIFICIAL INTELLIGENCE FOR INDUSTRIAL ENGINEERING
We are creating a new generation of industrial product design platform. Here, artificial intelligence and real-world simulations enable products to be born, evolve, and be validated within a high-performance and flexibly configurable digital platform.
FOCUS AREAS
- AI-Driven IC Design & SynthesisWe are pioneering methods to fundamentally transform integrated circuit design. Our research focuses on developing a multi-agent platform with solvers and approximators that can autonomously explore design spaces, predict circuit behavior, and generate optimized layouts from high-level specifications. The goal is to overcome the bottlenecks of traditional EDA tools and enable a new paradigm of synthesis-driven chip design.
- Generative Engineering & Topology SynthesisOur team is exploring the frontiers of computational design and optimization. We develop next-generation platform that translate functional requirements and physical constraints directly into optimal geometries. This research aims to create systems that automatically generate lightweight, strong, and efficient components, paving the way for designs that are impossible to conceive with traditional methods.
- Inverse Material Design & Microstructure EngineeringOur work involves creating AI-powered approximators and models that establish deep links between a material's composition, its microstructure, and its macroscopic properties. The ultimate objective is to enable the "inverse design" of new alloys, composites, and metamaterials with precisely tailored characteristics.
AI DRIVEN PLATFORM
AIDP IS A MULTI-LAYER PLATFORM THAT ENABLES ENGINEERING TEAMS TO CO-CREATE, OPTIMIZE, AND SYNTHESIZE COMPLEX ENGINEERING SOLUTIONS THROUGH AI-DRIVEN GENERATIVE DESIGN
- ENGINEERING Layer: Engineering Studio & Collaborative ScenesMulti-Team Collaboration: Powered by OpenUSD (Universal Scene Description), allowing teams to work on distinct scene layers simultaneously.
Experiment Orchestration: An intuitive editor for setting up optimization goals, refining existing solutions, or synthesizing entirely new industrial assets. - AI Agent Layer: RL Training & Cognitive SynthesisAgent Evolution: Specialized environments for training Reinforcement Learning agents to master complex engineering constraints.
Intelligent Design: Developing the "brains" behind generative synthesis, capable of navigating massive multi-dimensional design spaces. - Physics Layer: High-Fidelity Solvers & Neural ApproximatorsEncapsulated Physics: Advanced solvers and approximators wrapped into modular capsules for plug-and-play integration.
AI-Accelerated Simulation: Ultra-fast neural approximators that maintain physical accuracy at a fraction of the traditional compute cost. - Infrastructure Layer: Model Deployment & Performance ManagementScalable Operations: Seamless deployment of high-performance models across hybrid cloud environments.
Resource Orchestration: Real-time monitoring and optimization of computational workloads to ensure peak efficiency.
AIDP's models integrate seamlessly with industry-standard CAx and EDA ecosystems, empowering your current workflows with AI-driven synthesis without the need for infrastructure overhauls
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For research partnersWe are seeking leading scientific teams with deep expertise in computational physics and applied mathematics. Your knowledge is crucial for developing the foundational solvers at the heart of our platform. Let's collaborate to solve fundamental challenges and publish groundbreaking research that will redefine engineering design. -
For industry partnersWe invite forward-thinking engineering teams to help us build and validate our platform. Your domain expertise in industrial design is the critical link between our AI research and real-world application. Join us as a founding partner to integrate your challenges into our development cycle and gain a first-mover advantage with transformative technology.
If research is your thing, we're on the same path!
- Our vision is a future where artificial intelligence augments human ingenuity to solve the most complex challenges in industrial design. We're not just adapting to this change—we're building it.
- We're exploring one of the most compelling and applied fields in AI today: reinventing engineering design with reinforcement learning. Here, you'll dive deep into unsolved problems—from multi-agent systems in digital twins to heuristic planning in complex 3D environments. If you're driven by curiosity and want to see your research directly shape the future of manufacturing and design, this is your playground.
- We are on the lookout for curious minds and explorers who want to grow with a team of experts at the intersection of AI and complex engineering problem-solving. Join us and tackle unique challenges every day.
CURRENT OPPENINGS
We are looking for an ML Researcher with experience in Reinforcement Learning (RL) who is ready to work on innovative projects, analyze state-of-the-art approaches, and develop new algorithms. If you want to grow in cutting-edge technologies and solve complex challenges, join our team!
THE ROLE
YOUR SKILLS
BONUS POINTS FOR
THE ROLE
- Analysis of the latest scientific papers, research, and technological trends in Reinforcement Learning.
- Implementation of RL agents in Python using modern libraries such as PyTorch.
- Development and testing of new algorithms to improve agent training efficiency.
- Conducting experiments and analyzing their results to enhance model performance.
- Participation in research projects and implementation of innovative solutions.
YOUR SKILLS
- Strong programming skills in Python, including experience with machine learning libraries (PyTorch, NumPy, and others).
- Hands-on experience in Reinforcement Learning, including applying RL to practical problems (internships, research projects, or publications are considered relevant experience).
- Understanding of RL fundamentals, including popular algorithms (DQN, PPO, A3C, etc.).
- Ability to work in a team, communicate effectively, and share results.
BONUS POINTS FOR
- A Master's or PhD degree in Machine Learning, Artificial Intelligence, or related fields.
- Knowledge of and experience with JAX.
- Experience with Multi-Agent RL or developing multi-agent interaction systems.
- Publications in the field of Machine Learning or participation in scientific conferences.
We are looking for a Reinforcement Learning (RL) Engineer who is ready to grow and tackle challenging tasks within a team of professionals. If you are passionate about machine learning, enjoy working with 3D environments, and want to participate in the development and implementation of state-of-the-art AI solutions, we will be happy to see you on our team!
THE ROLE
OUR TECH STACK
Python / PyTorch / Ray RLlib / Jax / Numpy / Matplotlib / Pandas / MLflow / Docker / Kubernetes / Cosmos / Fenics
YOUR SKILLS
BONUS POINTS FOR
THE ROLE
- Implementation of Reinforcement Learning (RL) models based on modern algorithms.
- Training, fine-tuning, and optimization of RL models for solving practical problems.
- Working with 3D environments.
- Development of services for integrating machine learning models into production systems.
- Deploying trained models to a production environment and ensuring their stable operation.
OUR TECH STACK
Python / PyTorch / Ray RLlib / Jax / Numpy / Matplotlib / Pandas / MLflow / Docker / Kubernetes / Cosmos / Fenics
YOUR SKILLS
- Fundamental knowledge and practical experience with machine learning methods, including Reinforcement Learning.
- Proficiency in Python and core ML libraries (PyTorch, TensorFlow, or similar).
- Familiarity with DevOps fundamentals (Docker, Kubernetes) for model deployment is welcomed.
BONUS POINTS FOR
- Experience with RL frameworks (Ray Rllib, Stable-Baselines3, etc.).
- Understanding of distributed computing principles.
- Experience in developing REST API or microservices.
- Ability to write efficient code and perform code optimization.
- Basic knowledge and understanding of 3D graphics (experience with CAD systems and libraries).
- Experience in integrating ML models into 3D tools (e.g., OpenCascade, FreeCAD).
We invite experienced specialists in artificial intelligence, mathematicians, and scientists exploring physical and mathematical challenges to join our team for an exciting R&D project focused on advancing AI.
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