Jobs via Dice

Generative AI (GenAI) Design Engineer (Contract)

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Generative AI (GenAI) Design Engineer (Contract) in Santa Clara, CA. Required are a Master's or Ph.D. in Materials Science or related field, proficiency in Python/ML frameworks, and experience with generative AI and computational materials methods.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
December 5, 2025
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Santa Clara, CA
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🧠 - Skills detailed
#Python #AI (Artificial Intelligence) #PyTorch #Cloud #Deployment #ML (Machine Learning) #BI (Business Intelligence) #Automation #TensorFlow #HBase
Role description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Sapear Inc, is seeking the following. Apply via Dice today! Position : Generative AI (GenAI) Design Engineer (Contract) Location : Santa Clara, CA (Day 1 Onsite) Job Description : We are seeking a Generative AI (GenAI) 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. • 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. Required Skills & Qualifications • Education: Master's or Ph.D. in Materials Science, Computational 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. • Understanding of thermodynamics, crystallography, and mechanical properties of materials. Regards !! Bobby Sharma Talent Acquisition Lead Sapear Inc. Email : Cell : +1 Ext : 105 Mobile: +91 - We are hiring: