LLM Engineer - Open Source LLM Tuning
Location: Austin, TX (Hybrid)
About Us: We're a dynamic early-stage start-up based in Austin, committed to pushing the boundaries of AI. Our team is dedicated to developing cutting-edge solutions by fine-tuning open-source large language models (LLMs). We're looking for a talented LLM Engineer to join our innovative team and contribute to our mission of advancing AI technologies.
Role Overview: As a LLM Engineer, you will be at the forefront of our AI initiatives, focusing on the fine-tuning of open-source LLMs. Your expertise will help us enhance our models to deliver exceptional performance and accuracy. Ideal candidates will have hands-on experience with distributed machine learning model training and federated learning. Experience in a start-up environment is highly desirable, as it will enable you to thrive in our fast-paced and collaborative setting.
Key Responsibilities:
• Fine-tune open-source large language models (LLMs) to meet specific project requirements.
• Design and implement distributed machine learning training frameworks.
• Explore and apply federated learning techniques to improve model performance and data privacy.
• Collaborate closely with cross-functional teams to integrate AI solutions into our products.
• Conduct research and stay updated with the latest advancements in AI and machine learning.
Qualifications:
• Proven experience in fine-tuning and deploying open-source LLMs.
• Strong background in distributed machine learning model training.
• Familiarity with federated learning techniques.
• Experience working in a start-up environment is a plus.
• Proficiency in Python and ML frameworks such as TensorFlow or PyTorch.
• Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
• Strong communication skills to effectively convey complex technical concepts.
Location: Austin, TX
Posted: Aug. 26, 2024, 1:55 a.m.
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