
LLM Engineer Singapore Non-Remote
4 days ago
We are seeking a proactive Large Language Model (LLM) Engineer to lead the development of text generation systems. The ideal candidate will possess a deep understanding of deep learning and advanced NLP techniques.
Key Responsibilities:
- Architect and fine-tune large language models to generate synthetic text grounded to the statistics of a set of tabular data.
- Collaborate with cross-functional teams, including AI researchers and engineers, to integrate LLM solutions into existing synthetic data generation pipelines.
- Stay updated on the latest advancements in LLMs, ensuring our solutions remain at the forefront of technology.
- Implement prompt engineering strategies to enhance the quality and relevance of generated text.
- Be familiar with finetuning open weights model like Qwen-2, Llama-3, Mistral for Instruction finetuning and DPO.
- Be familiar with training frameworks like TRL, Unsloth, Hugging face ecosystem etc.
- Evaluate and optimize model performance.
- Develop and maintain comprehensive documentation for model architectures, training recipes and deployment procedures.
Essential Skills and Qualifications:
High Priority:
- Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
- Proven experience in developing and deploying large language models, with a focus on text generation.
- Strong understanding of LLM and deep learning techniques, such as Prompt Engineering, Fine-Tuning, RAG, LoRA, etc.
- Strong proficiency in programming languages including Python and deep learning frameworks like PyTorch and Tensorflow.
- Familiarity with prompt engineering techniques and their application in enhancing LLM outputs.
- Excellent problem-solving skills and the ability to work collaboratively in a fast-paced startup environment.
- Strong communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
- Quick learner, able to quickly learn and follow new advancements in industry and academia and evaluate and
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