Ai Hardware Design Engineer

Santa Clara, CA, US • Posted 5 hours ago • Updated 1 hour ago
Contract Independent
Contract W2
On-site
$Market
Fitment

Dice Job Match Score™

⭐ Evaluating experience...

Job Details

Skills

  • Innovation
  • Product Design
  • Chemical Vapor Deposition
  • Mapping
  • Chemistry
  • Business Intelligence
  • Physics
  • Computational Fluid Dynamics
  • Control Flow Diagram
  • Heat Transfer
  • Docker
  • Kubernetes
  • Optimization
  • Workflow
  • Collaboration
  • Computer Science
  • Electrical Engineering
  • Artificial Intelligence
  • Python
  • PyTorch
  • TensorFlow
  • Generative Artificial Intelligence (AI)
  • DFT
  • Modeling
  • Machine Learning Operations (ML Ops)
  • HPC
  • Cloud Computing
  • Publications
  • Bridging
  • Hardware Development
  • Machine Learning (ML)

Summary

Role: AI Hardware Design Engineer

Location: Santa Clara CA. Onsite opportunity

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.

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.

Regards,

Praveen

Tel:

Email:

Infobahn SoftWorld Inc.,

San Jose, CA 95131.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: infobahn
  • Position Id: 2026-61080
  • Posted 5 hours ago
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