AI Engineer

AI Engineer - TechM189000

Location: Santa Clara, CA onsite

Client: Tech M / Applied Material

About the Role:

We are seeking a highly skilled and innovative AI Engineer to join our team and lead the development of intelligent AI agents and RAG-based applications, with hands-on experience in building scalable, production-grade GenAI systems.

Key Responsibilities:

• Demonstrate advanced programming expertise, particularly in Python, with deep proficiency in AI-centric libraries such as TensorFlow and PyTorch.
• Architect and implement Retrieval-Augmented Generation (RAG) pipelines to enhance model performance using external knowledge sources.
• Design, develop, and deploy AI agents capable of autonomous decision-making and task execution using LLMs and multi-modal models.
• Implement and manipulate complex algorithms essential for developing and optimizing generative AI models.
• Manage data pipelines involving data pre-processing, augmentation, and synthetic data generation to enhance model training and performance.
• Ensure robust data handling practices including cleaning, labeling, and structuring datasets for generative AI workflows.

Required Qualifications:

• Bachelor's or master's degree in computer science, AI/ML, or related field.
• 3+ years of experience in AI/ML engineering, with at least 1 year focused on Generative AI.
• Hands-on experience with RAG architectures, including document chunking, embedding generation, and retrieval systems.
• Proficiency in Python and familiarity with libraries such as Hugging Face, Transformers, OpenAI API, and PyTorch or TensorFlow.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Strong understanding of LLM capabilities, limitations, and prompt engineering techniques.

Preferred Qualifications:

• Experience with fine-tuning LLMs or training custom models.
• Familiarity with multi-modal AI (text, image, audio).
• Contributions to open-source GenAI projects or publications in AI conferences.
• Experience with CI/CD pipelines for ML model deployment.

Notes:

Should have experience of conducting ML based analysis and simulations on different hardware with varying parameters

OR

Should have experience of conducting ML based analysis and simulations on Fluid Mechanics with varying parameters

OR

Should have experience of conducting ML based analysis and simulations on Material Science with varying parameters

This field is called "Material Informatics"

Material Flow

Search for people in "Computational Chemistry"

"DFT" – Density Functional Theory