LLM scientist

Job Overview

Pranatree LLC is seeking an experienced LLM Scientist to join our team, focusing on the development, fine-tuning, and deployment of cutting-edge Large Language Models (LLMs) and Generative AI solutions. This role requires a strong foundation in data science, AI, and software engineering, with a particular emphasis on building innovative solutions for complex, unstructured problems. The position is remote and involves working on high-impact projects that push the boundaries of what LLMs can achieve.

Key Responsibilities

LLM Fine-Tuning and Development: Research, fine-tune, and deploy LLMs, optimizing their capabilities to solve diverse AI problems.

Generative AI Solutions: Leverage advanced AI and machine learning techniques to build prototypes and production-grade solutions for various use cases.

RAG Pipelines: Design and implement Retrieval-Augmented Generation pipelines to improve the accuracy and relevance of AI outputs.

Prototyping: Build and demonstrate working prototypes using frameworks such as Streamlit or Dash.

Algorithm and Data Structures Expertise: Apply strong knowledge of algorithms and data structures to parse and process unstructured data effectively.

System Performance and Debugging: Profile, debug, and optimize machine learning systems for scalability and performance in large-scale environments.

Collaboration and Problem Solving: Work collaboratively with data scientists, engineers, and cross-functional teams to solve unstructured, complex problems using AI.

Communication: Communicate technical concepts and project updates clearly and effectively to stakeholders.

Qualifications and Requirements

Education: Bachelors degree in Computer Science, Information Technology, or a related field (or equivalent work experience).

Experience:

Minimum of 5 years of experience in software development, including relevant work in AI and machine learning.

Technical Skills:

Programming Proficiency: Strong coding skills in Python, Java, or C++.

Data Science and AI: Solid foundation in data science and experience with Generative AI.

LLM Expertise: Experience with fine-tuning large language models and familiarity with RAG pipelines.

Frameworks for Prototyping: Proficiency in building prototypes using Streamlit, Dash, or similar app frameworks.

Algorithms and Data Structures: Strong background in algorithms, data structures, and parsing unstructured data.

System Performance: Experience with profiling, debugging, and ensuring the scalability of machine learning systems.

Preferred Experience: Hands-on experience with Generative AI and fine-tuning LLMs.

Soft Skills:

Strong communication skills to convey complex technical ideas.

Problem-solving ability, especially in unstructured and ambiguous scenarios.

Performance Expectations

Develop and fine-tune LLMs for various applications, ensuring high performance and reliability.

Design and deploy prototypes that showcase practical uses of LLMs and Generative AI.

Collaborate effectively within a multidisciplinary team to develop innovative AI-driven solutions.

Ensure scalable and high-performance AI systems through effective profiling and debugging practices.

Maintain clear documentation and provide regular updates to team members and stakeholders.