As an LLM Data Scientist, you will be responsible for designing, developing, and deploying advanced NLP systems that leverage cutting-edge AI technologies. Your work will focus on areas like prompt engineering, agent-based AI, Retrieval-Augmented Generation (RAG), and optimizing large language models for performance and efficiency. You will also collaborate with cross-functional teams to tackle challenges related to AI ethics, safety, and risk mitigation.
Your role
- Design and implement next-generation agent-based AI systems utilizing large language models (LLMs).
- Conduct prompt engineering to optimize the interaction between AI models and tasks.
- Work on Retrieval-Augmented Generation (RAG) and information retrieval to enhance AI system capabilities.
- Perform comprehensive LLM evaluation, including alignment, safety, applicability, and knowledge assessments.
- Fine-tune and optimize LLMs using advanced techniques like LoRA and QLoRA to improve inference efficiency and performance.
- Collaborate with teams across disciplines to address ethical, safety, and risk-related issues surrounding AI deployment.
Offer
- Long-term freelance contract
- Solid market rates depending on seniority
- Access to top-notch projects
Requirements
- Prompt Engineering: Expertise in designing prompts to optimize AI task performance.
- AI Performance Analysis: Experience in evaluating and analyzing the performance of AI models.
- LLM Evaluation: Proficiency in evaluating LLMs for knowledge, alignment, safety, and overall applicability.
- Natural Language Understanding (NLU): Hands-on experience with NLU libraries and tools such as NLTK or models like GPT-3.
- LLM Inference Tuning: Skilled in optimizing LLM inference using techniques like LoRA or QLoRA for greater efficiency.
- LLM Fine-Tuning: Experience in fine-tuning large language models to improve specific task performance.
- Cloud Platforms: Proficiency in working with cloud services (Azure, GCP, AWS) for deploying and managing AI models.
Nice-to-Have Skills:
- GCP Toolset: Familiarity with Google Cloud tools like BigQuery, Dataflow, Dataproc, Vertex AI, and Pub/Sub for processing and analyzing large datasets.
- Advanced AI Research: Interest in staying updated with the latest advancements in AI, including ethical AI and responsible AI usage.