gem
Principal LLM Application Engineer
System Two Security
Remote, USA
Full-time
Senior · 5+ years experience
Remote
Discovered 1 weeks ago
PythonRCloudDevOpsRAGLLM
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PythonRCloudDevOpsRAGLLM
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- Development and Optimization of LLMs: Implement and fine-tune state-of-the-art Large Language Models for various applications, focusing on performance and accuracy.
- Evaluating Model Performance: Conduct rigorous evaluations of LLMs, assessing effectiveness, efficiency, and business alignment.
- Integration of Advanced AI Technologies: Implement Retrieval-Augmented Generation (RAG), function calling, and code interpreter technologies to enhance the capabilities of Large Language Models.
- Research and Development: Stay abreast of the latest advancements in machine learning, particularly in LLMs, LLM agents, and large-scale neural network training.
- Data and Model Parallel Training: Utilize data and model parallel training techniques for efficient handling of large-scale models.
- Cross-Functional Collaboration and Leadership: Work with ML engineers, data scientists, and product teams, providing guidance and mentorship.
- Documentation and Reporting: Maintain detailed documentation of methodologies, models, and results, communicating findings across the organization.
- Contribute to product roadmap and vision
- Implement and evaluate various LLM application logic ( flows ) and prompting strategies and stay up to date with the latest advancements in this field
- Lead the incubation of new initiatives, architect scalable solutions, and drive strategic technology choices to develop and deliver AI/ML capabilities in a micoservcies architecture for our customers.
- Design, test, and deploy Machine learning models, including large-language models and build pipelines at scale for batch and real-time use cases.
- Bachelor's degree in Computer Science, Engineering, or related field.
- 5+ years of experience in natural language processing, machine learning, and/or data science.
- Experience in Python or R.
- Experience working with large language models, such as GPT-3+, LLAMA, or similar.
- Strong problem-solving skills and the ability to think creatively to identify new opportunities for LLMs in our products and services.
- Experience with one or more deep learning frameworks.
- A deep theoretical or empirical understanding of deep learning.
- Experience in building, testing and deploying machine learning models, including large language models.
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