Position: AI Engineer
Location: Santa Clara, CA***Day 1 Onsite***
Duration: 1 Years
AI Engineer all profile rejected need more
With good experience in LLL
PhD on ML, Data science and LLM
Mandatory Areas
Must Have Skills
Skill 1 Demonstrate advanced programming expertise, particularly in Python, with deep proficiency in AI-centric libraries such as TensorFlow and PyTorch.
Skill 2 Design, develop, and deploy AI agents capable of autonomous decision-making and task execution using LLMs and multi-modal models
Skill 3 Hands-on experience with RAG architectures, including document chunking, embedding generation, and retrieval systems
Good To have Skills
Skill 1 Familiarity with multi-modal AI (text, image, audio)..
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. This role is ideal for someone passionate about pushing the boundaries of applied AI, 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.
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