AI Hardware Design Engineer

Pentangle Tech Services | P5 Group; Santa Clara (CA); In loco; USD 150.000 - 210.000; Tempo pieno

Descrizione del lavoro

AMAT is seeking an Ai Hardware Design Engineer in Santa Clara to design, develop, and optimize generative AI models and workflows for advanced manufacturing and product design.

You will implement surrogate models, inverse-design strategies, and digital twins, collaborating with physicists and software engineers to ensure designs are manufacturable and robust in high-performance computing environments.

Competenze

• Master’s or Ph.D. in Computer Science, Computational/Electrical Engineering, AI/ML, or related field.
• Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow).
• Familiarity with MLOps, HPC environments, and cloud deployment.

Mansioni

• Develop forward surrogate models for chamber mapping and multi-parameter optimization.
• Implement inverse-design workflows using generative/adjoint/topology optimization methods.
• Build bi-directional models to infer process parameters and geometry modifications.
• Create high-fidelity digital twins combining physics-based solvers with learned components.
• Maintain containerized MLOps systems (Docker, Kubernetes) in HPC environments.
• Develop multi-objective optimization and uncertainty-quantification workflows.
• Collaborate with physicists, domain experts, and software engineers to ensure physical laws compliance.

Conoscenze

Python

PyTorch

TensorFlow

Generative AI

Formazione

Master’s or Ph.D. in Computer Science/Engineering/AI

Strumenti

Docker

Kubernetes

HPC

Descrizione del lavoro

Job Description

We are seeking an Ai Hardware Design Engineer to join our team and drive innovation in AI-powered solutions. This role involves designing, developing, and optimizing generative AI models and workflows for applications such as product design, and intelligent automation.

• Develop forward surrogate models for CVD/ALD/etch chambers mapping geometry, gas chemistry, flow, temperature, and power to film-uniformity, step-coverage, particle behavior, and thermal outcomes.
• Implement inverse-design workflows where target performance specifications generate feasible chamber geometries, showerhead/baffle designs, and process conditions via generative or adjoint/topology-optimization methods.
• Build bi-directional models that infer optimal process parameters for a given geometry and recommend geometry modifications when process latitude is insufficient.
• Create high-fidelity digital twins combining physics-based solvers (CFD, plasma, heat transfer) with learned surrogate components for rapid design-space exploration.
• Platform & MLOps Infrastructure: Implement and maintain robust, containerized MLOps systems (Docker, Kubernetes) in HPC environments to deploy models efficiently.
• Develop robust multi-objective optimization and uncertainty-quantification workflows to ensure AI-generated designs are manufacturable, robust to variation, and compatible with downstream yield requirements.
• Collaborate with physicists, domain experts, and software engineers to validate that AI models comply with fundamental scientific laws.

Job Description

We are seeking an Ai Hardware Design Engineer to join our team and drive innovation in AI-powered solutions. This role involves designing, developing, and optimizing generative AI models and workflows for applications such as product design, and intelligent automation.

• Develop forward surrogate models for CVD/ALD/etch chambers mapping geometry, gas chemistry, flow, temperature, and power to film-uniformity, step-coverage, particle behavior, and thermal outcomes.
• Implement inverse-design workflows where target performance specifications generate feasible chamber geometries, showerhead/baffle designs, and process conditions via generative or adjoint/topology-optimization methods.
• Build bi-directional models that infer optimal process parameters for a given geometry and recommend geometry modifications when process latitude is insufficient.
• Create high-fidelity digital twins combining physics-based solvers (CFD, plasma, heat transfer) with learned surrogate components for rapid design-space exploration.
• Platform & MLOps Infrastructure: Implement and maintain robust, containerized MLOps systems (Docker, Kubernetes) in HPC environments to deploy models efficiently.
• Develop robust multi-objective optimization and uncertainty-quantification workflows to ensure AI-generated designs are manufacturable, robust to variation, and compatible with downstream yield requirements.
• Collaborate with physicists, domain experts, and software engineers to validate that AI models comply with fundamental scientific laws.

Job Title: AI Hardware Design Engineer

Location: Santa Clara, CA

Duration: Long Term

Client: AMAT

Required Skills & Qualifications

• Education: Master’s or Ph.D. in Computer Science, Computational/Electrical Engineering, AI/ML, or related field.
• Technical Expertise:
  • Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow).
  • Experience with generative AI (LLMs, diffusion models, graph-based models).
  • Knowledge of computational materials methods (DFT, MD, phase-field modeling).
• Additional Skills:
  • Familiarity with MLOps, HPC environments, and cloud deployment.
  • Proven experience (code repos, publications) bridging simulation software, hardware design, and ML.