Applied Scientist (LLM)
- Джерело:
- djinni.co
Що робити
- Design and implement advanced methods in prompt orchestration, fine-tuning (SFT/RLHF/DPO), and autonomous agentic workflows
- Curate high-quality training data from large-scale text and multi-modal sources
- Identify patterns in model hallucinations and visualize evaluation metrics for clear interpretation
- Tune hyperparameters and improve inference speed/accuracy through PEFT (LoRA/QLoRA) and advanced prompt engineering
- Collaborate with Product and Data Engineering teams to seamlessly integrate LLM features into the broader ecosystem
Що очікуємо
- 4+ years of commercial experience in Machine Learning, with a specific focus on the NLP or LLM domain
- Strong knowledge of Python3, NumPy, pandas, and modern text-processing libraries, PyTorch and Hugging Face (Transformers, PEFT, Accelerate)
- Proficiency in PEFT/LoRA and Reinforcement Learning techniques
- Deep understanding of attention mechanisms, tokenization, context window management, and embedding spaces
- Practical experience in at least one of the following: Retrieval-Augmented Generation (RAG), — Fine-tuning, or Agentic frameworks
Що пропонуємо
- Practical experience with Pinecone, Weaviate, Milvus, or Chroma
- Advanced quantization (GGUF, AWQ, EXL2), pruning, and knowledge distillation
- Experience with LangChain, LlamaIndex, or AutoGen
- Basic understanding of web/client-server architecture and streaming API responses (Asyncio, aiohttp)
- Familiarity with RAGAS, DeepEval, or G-Eval
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