| LLM Applied Al & Gen Al at Mountain View, California, USA |
| Email: [email protected] |
| From: saloni chaurasia, tekinspirations [email protected] Reply to: [email protected] Hi, I Hope you are doing great. Please find below position if you have any matching candidate as per requirement. Please send me updated resume with candidate information. Job Details Role: LLM Applied Al & Gen Al Duration: 12 month Location: Mountain View, CA (PST Zone candidate only considered) Job Type Onsite MOI Virtual Minimum Qualifications: Masters degree/PhD in Computer Science & Data Science/Al ML or a related technical field or equivalent practical experience. Experience with LLM/Gen Al frameworks, libraries like Lang Chain and tools Understanding of machine learning concepts and best practices Programming experience with Python Familiarity with Applied Al use cases and solutions Excellent communication and collaboration skills Experience with deep learning frameworks (e.g. PyTorch, TensorFlow) is a plus. Skills: This role combines expertise in Large Language Models (LLMs) with Generative Al (Gen Al) to develop and implement innovative solutions. You'll be at the forefront of Al technology, applying your skills to real-world problems. Here's a breakdown of the typical responsibilities: Research and Development Conduct research to push the boundaries of LLMs and Gen Al Design and implement algorithms for LLM training and Gen Al tasks Stay up-to-date on the latest advancements in LLM and Gen Al research Prompt Engineering and Prompt chains Fine-tune LLM models for specific applications Develop and integrate Gen Al models into various applications Optimize models for performance, scalability, and efficiency Deploy models into production environments Applications and Use Cases Regards, Saloni Chaurasia { Technical Recruiter } TEK Inspirations LLC Pvt. Ltd. | 13573 Tabasco Cat Trail, Frisco, TX 75035, United States E-Mail: [email protected] Keywords: machine learning Alabama California Texas LLM Applied Al & Gen Al [email protected] |
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| Thu Mar 28 03:50:00 UTC 2024 |