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Researcher to design and run ablation experiments that shape the pretraining data mix for a frontier LLM, turning hypotheses into measurable gains on public benchmarks.
ML engineer builds and runs online reinforcement-learning pipelines to improve GigaChat’s post-training, designing experiments, reward signals, and distributed training workflows.
Lead the online reinforcement learning team for STEM-focused LLM post-training at GigaChat, designing RLHF pipelines, reward models, and data curation to improve reasoning in math, physics, and other sciences.
Lead the online reinforcement-learning team for GigaChat, designing post-training methods, reward models, and data pipelines to make the LLM more helpful and user-friendly.
Build and optimize large-scale generative language models (LLMs) for GigaChat, focusing on Russian-language performance, distributed training, and efficiency improvements.
Build and deploy AI agents for process optimization in banking, focusing on NLP tasks like semantic search, classification, and LLM fine-tuning (SFT, RAG) using Python and frameworks like PyTorch and LangChain.
Senior data scientist leading a small team to build and improve an AI copilot for bank staff, focusing on LLM/NLP models for risk management and customer dialogue.
Builds and scales ML services, pipelines, and AI agents to extract insights from customer interactions across banking and ecosystem surfaces using Python, FastAPI, and ML/LLM stacks.
ML engineer builds and deploys GenAI solutions—chatbots, RAG pipelines, and AI agents—using Python, PyTorch, LangChain, and LangGraph.
NLP engineer working on GigaChat Pro, a bank employee copilot assistant that interacts with clients. Daily tasks include developing LLM/BERT-based models, optimizing pipelines, and testing new AI-driven business solutions to enhance the assistant’s functionality and performance.
Build and improve deep-learning models to detect audio deepfakes, using PyTorch and modern audio feature pipelines like spectrograms and wavelets.
ML Engineer role focusing on Online RL and Post-Training LLM, responsible for developing methods, conducting experiments, and improving model quality at Сбер in Moscow.
Senior Research Engineer focused on large language model pretraining, optimizing training recipes, architectures, and distributed training infrastructure using PyTorch on H100/B200 clusters.
Lead the architecture and pretraining of large language models for GigaChat, designing MoE and Transformer-based models, scaling laws, and long-context features on H100/B200 clusters.
Lead a team to optimize and scale the reinforcement learning pipeline for GigaChat, focusing on speed, stability, and cost-efficiency of online RL/RLHF/RLVR training and inference.
Leads a team to improve large language models by designing training pipelines, curating datasets, and evaluating model quality for business use cases.
ML engineer builds and runs online reinforcement learning pipelines for a Russian LLM, designing experiments, optimizing GPU throughput, and improving model quality from research to production.
Lead a data science team to enhance Sberbank Online’s AI Assistant by integrating LLM-powered search, optimizing models, and driving product strategy with production-grade MLOps.
Develops and reviews AI-driven audit tools, focusing on GenAI, RAG systems, and LLM fine-tuning for internal audit platforms.
Senior Data Scientist builds time-series and tabular ML models to forecast deposit elasticity and loan prepayments for corporate clients, using Python, PySpark, and ML libraries.
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