Overview
Skills
Job Details
Hello ,
Greetings for the day !
I hope you are doing well.
My name is Vinayak, and I am a Technical Recruiter from Empower Professionals Inc. I came across your profile and wanted to reach out regarding an "AI Engineer" role with one of our clients. And it s based out in Santa Clara, CA (Hybrid).
Please let me know if you are available in the market and interested in this role (see job description below) - if so, we can connect and speak further.
Role: AI Engineer
Locations: Santa Clara, CA (Hybrid)
Duration: 12+ Months Contract
Job Description:
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.
Responsibilities:
- Demonstrate advanced programming expertise, particularly in Python, with deep proficiency in AI-centric libraries such as Tensor Flow 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, Google Cloud Platform) 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.