Data Scientist (LLM Experience)

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: Bachelor’s 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.

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: Bachelor’s 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.