Web3 Jobs & Crypto Jobs Where crypto teams hire. Where builders get found.
The #1 crypto-native job board for web3 jobs, crypto jobs & blockchain vacancies. Every role in the ecosystem — dev, design, marketing & more. Remote-first at top protocols, DAOs & companies.
By using web3vacancy you agree to our Terms of Service and Privacy Policy.
Latest Crypto Job Vacancies
No applications. Teams find and message you directly.
Sber is looking for a Senior NLP/LLM Engineer to develop AI-copilot systems for premium client managers, transitioning from classic NLP solutions to adaptive multi-agent systems.
The AI development team at Sber is seeking an NLP/LLM Engineer to enhance AI-copilot systems for premium client managers. The team is moving from traditional NLP solutions to adaptive multi-agent systems.
Responsibilities
- Design and implement end-to-end LLM pipelines, including advanced RAG systems and autonomous AI agents (planning, function calling, multi-agent orchestration)
- Fine-tuning and adaptation: SFT/RLHF/DPO, LoRA/QLoRA for business tasks; determine when fine-tuning is needed versus prompt engineering or RAG
- Maintain quality culture: implement product and ML metrics (RAGAS, DeepEval, LLM-as-a-Judge), automate regression testing
- Write clean, documented, and testable Python code, design API contracts for ML components
- Participate in code reviews, establish technical standards for the team, work directly with the product and stakeholders
Requirements
- 4+ years of experience in DL/NLP, including training and fine-tuning models on PyTorch, with at least 1 year of practical experience with LLM
- Practical experience building AI agents and LLM pipelines using LangChain/LangGraph
- Deep understanding of modern LLM architecture: attention, MoE, RoPE, KV-cache, alignment methods (RLHF/DPO), principles of efficient inference
- Strong engineering culture: Python (asyncio, pydantic, fastapi), clean testable code (pytest), asynchronous microservices; understanding of Docker/K8s, CI/CD for ML
- Evaluation and monitoring: proficient with LLMOps tools (Arize, LangSmith, W&B, Phoenix), experience creating custom eval pipelines
- Data handling: experience preprocessing complex data for datasets, knowledge of SQL