Data Science (LLM/NLP)

Join T1 as a Data Scientist focusing on LLM and NLP. Work on integrating LLM into products, optimizing performance, and collaborating with product and ML teams.

• •Integrating LLM into products and services (API, backend, data processing pipelines);
• •Evaluating model response quality (automatic metrics, human eval);
• •Ensuring safety, filtering, and compliance with ethical requirements (guardrails);
• •Building RAG systems: data indexing, working with vector databases, optimizing search and generation quality;
• •Collaborating with product and ML teams, participating in architectural decisions;
• •Optimizing performance and cost of inference (quantization, batching, caching);
• •Working with multimodal models (text, images, documents — if necessary);
• •Designing, training, and fine-tuning LLM (fine-tuning, instruction tuning).

• •Higher education (IT, technical, mathematical);
• •Proficient in Python, SQL;
• •Good knowledge of probability theory, mathematical statistics, machine learning algorithms;
• •Knowledge of NLP algorithms;
• •Understanding of LLM workings and how fine-tuning and inference occur;
• •Experience deploying ML/LLM solutions (Docker, Kubernetes, cloud);
• •Experience with prompt engineering, fine-tuning / PEFT (LoRA, adapters), RAG approaches;
• •Experience implementing agent scenarios;
• •Experience with vector databases: optimizing indexes, queries;
• •Experience with frameworks: LangChain, LlamaIndex, Hugging Face;
• •Knowledge of LLM evaluation methods (BLEU, ROUGE, MMLU, custom evals);
• •Experience optimizing inference (vLLM, TensorRT, ONNX);
• •Experience with multimodal models;
• •Proficient in Python.