AI Hardware Design Engineer - Santa Clara, CA (Hybrid)

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Role: AI Hardware Design Engineer

Location: Santa Clara, CA (Hybrid)

Duration: 12 Months

Responsibilities:

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 content creation, 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.
  
  

Requirements:

• 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.
  

In compliance with the salary transparency law, the expected pay range for this role is $50. Actual compensation depends on experience and interview evaluation.

Best Regards,

Vaibhav Karhiwale

Sr. Technical Recruiter | Empower Professionals

| Phone: x 348