AI Hardware Design Engineer

Santa Clara, CA, US • Posted 2 hours ago • Updated 2 hours ago

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🛠️ Calibrating flux capacitors...

Job Details

Skills

Artificial Intelligence
Bridging
Business Intelligence
Chemical Vapor Deposition
Chemistry
Cloud Computing

Summary

We are looking for AI Hardware Design Engineer for our client in Santa Clara, CA

Job Title: AI Hardware Design Engineer

Job Location: Santa Clara, CA

Job Type: Contract

Job Overview:

Pay Range: $62hr - $67hr

Develop forward surrogate models for CVD/ALD/etch chambers mapping geometry, gas chemistry, flow, temperature, and power tfilm-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 tdeploy models efficiently.
Develop robust multi-objective optimization and uncertainty-quantification workflows tensure AI-generated designs are manufacturable, robust tvariation, and compatible with downstream yield requirements.
Collaborate with physicists, domain experts, and software engineers tvalidate that AI models comply with fundamental scientific laws.

Required Skills And 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.

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: 10516350
Position Id: CA_AHDE_0401
Posted 2 hours ago

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