AI Engineer
Bucharest, Bucharest, Romania
R
RON 264K-396K (estimate) Senior-level Full Time
Tasks
- Adapt and fine tune small language models using LoRA and QLoRA
- Build production NLP LLM and multi agent applications
- Deploy and optimize fine tuned models on proprietary infrastructure
- Design and implement hybrid retrieval architectures
- Evaluate model outputs for factual grounding and compliance
- Evaluate scope propose and build customer protection features
- Implement Cache Augmented Generation CAG
- Implement Knowledge Augmented Generation KAG
- Implement LLM observability and evaluation tools
- Implement Retrieval-Augmented Generation (RAG)
- Incorporate GenAI ML into product design
- Ingest and consume data using Model Context Protocol MCP
- Monitor latency token consumption and agent behavior
- Serve and scale fine tuned open weights models using vLLM
- Translate agentic workflows into maintainable software architectures
- Use vector databases and knowledge graphs for grounded context
Perks/Benefits
- 25 vacation days
- Focus Fridays
- Generous leave package
- Hybrid work
- LinkedIn Learning
- Meal vouchers
- Peer recognition platform
- Private medical subscription
- Volunteering days
- Work anniversary day off
Skills/Tech-stack
API Architecture | AWS | Agent systems | Apache Spark | Azure | Cache Augmented Generation | Databricks | Deep learning | Fine Tuning | GCP | Knowledge graphs | Knowledge-Augmented Generation | LLM Observability | LLM orchestration | LoRA | Model Context Protocol | Model Fine-tuning | Model Quantization | Multi-Agent | Multi-Agent Systems | Multi-tenant | Multi-tenant architecture | NLP | Python | QLoRA | REST API | Retrieval-Augmented Generation | Snowflake | Tenant architecture | Transformers | VLLM | Vector Databases
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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