Applied Scientist (LLM)

<h4>Team Summary</h4> <p>Our distributed team is looking for an experienced Applied Scientist with a strong background in Large Language models to develop high-performance Generative AI features across Cloud and Edge environments.</p> <h4>Job Summary</h4> <p>In this role you will drive the transition from research to production by optimizing local inference through model compression and quantization for private, real-time Edge performance, while also engineering scalable RAG architectures and multi-agent systems for Cloud deployment. Your daily responsibilities encompass the full research lifecycle, including formulating hypotheses, generating synthetic datasets, fine-tuning LLMs, and validating safety and alignment, ultimately culminating in technical reports.</p> <h4>Responsibilities and Duties</h4> <ul> <li>Design and implement advanced methods in prompt orchestration, fine-tuning (SFT/RLHF/DPO), and autonomous agentic workflows</li> <li>Curate high-quality training data from large-scale text and multi-modal sources</li> <li>Identify patterns in model hallucinations and visualize evaluation metrics for clear interpretation</li> <li>Tune hyperparameters and improve inference speed/accuracy through PEFT (LoRA/QLoRA) and advanced prompt engineering</li> <li>Collaborate with Product and Data Engineering teams to seamlessly integrate LLM features into the broader ecosystem</li> <li>Track and report progress using industry-standard benchmarks (MMLU, HumanEval, etc.) and custom internal KPIs</li> <li>Stay at the forefront of the field (e.g., State Space Models, new Transformer variants) and evaluate cutting-edge techniques for production readiness</li> <li>Engage in continuous technical growth and mentor junior colleagues to elevate the team's expertise<strong>&nbsp;</strong></li> </ul> <h4>Qualifications and Skills</h4> <ul> <li>3+ years of commercial experience in Machine Learning, with a specific focus on the NLP or LLM domain</li> <li>Strong knowledge of Python3, NumPy, pandas, and modern text-processing libraries, PyTorch and Hugging Face (Transformers, PEFT, Accelerate)</li> <li>Proficiency in PEFT/LoRA and Reinforcement Learning techniques</li> <li>Deep understanding of attention mechanisms, tokenization, context window management, and embedding spaces&nbsp;</li> <li>Practical experience in at least one of the following: Retrieval-Augmented Generation (RAG), Fine-tuning, or Agentic frameworks</li> <li>Proven ability to manage and analyze massive datasets (&gt;100GB) across text, image, and audio formats</li> <li>Hands-on experience crafting high-fidelity datasets and building robust data pipelines</li> <li>Expertise in prompt engineering, agentic framework design, and LLM pipeline orchestration</li> <li>Experience deploying LLMs to production environments using Triton Inference Server, vLLM, TGI, or ONNX</li> <li>Good written and spoken English</li> </ul> <h4>Nice to have</h4> <ul> <li>Practical experience with Pinecone, Weaviate, Milvus, or Chroma&nbsp;</li> <li>Advanced quantization (GGUF, AWQ, EXL2), pruning, and knowledge distillation</li> <li>Experience with LangChain, LlamaIndex, or AutoGen</li> <li>Basic understanding of web/client-server architecture and streaming API responses (Asyncio, aiohttp)</li> <li>Familiarity with RAGAS, DeepEval, or G-Eval</li> <li>Experience using Docker, Kubernetes, and cloud GPU orchestration (e.g., Run:ai, Lambda Labs)</li> <li>Knowledge of C++, Triton, or CUDA for custom kernel development</li> </ul> <h4>We offer multiple benefits that include</h4> <ul> <li>The environment of equal opportunities, transparent and value-based corporate culture and an individual approach to each team member</li> <li>Competitive compensation and perks</li> <li>Gig-contract</li> <li>21 paid vacation days per year, paid public holidays according to the Ukrainian legislation</li> <li>Development opportunities like corporate courses, knowledge hubs, and free English classes as well as educational leaves</li> <li>Medical insurance is provided from day one. Sick leaves and medical leaves are available</li> <li>Remote working mode is available within Ukraine only</li> <li>Free meals, fruits, and snacks when working in the office.</li> </ul>