SQUAD

Applied Scientist (LLM)

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SeniorHybryda·WrocławFull-time·Umowa o pracę

#380557·Dodano 4 miesiące temu·1

Źródło: justjoin.it

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Tech Stack / Keywords

Machine Learning LLM Python

Podsumowanie oferty

The role involves developing and optimizing Large Language Models (LLMs) for real-time Edge and Cloud deployment. Responsibilities include model compression, quantization, fine-tuning, and engineering scalable architectures. The position requires driving the transition from research to production and collaborating with product and data teams.

Wymagania

3+ years of commercial experience in Machine Learning, focusing on NLP or LLM
Strong knowledge of Python3, NumPy, pandas, PyTorch, Hugging Face (Transformers, PEFT, Accelerate)
Proficiency in PEFT/LoRA and Reinforcement Learning techniques
Deep understanding of attention mechanisms, tokenization, context window management, and embedding spaces
Practical experience with Retrieval-Augmented Generation (RAG), Fine-tuning, or Agentic frameworks
Ability to manage and analyze large datasets (>100GB) across text, image, and audio
Experience building high-fidelity datasets and robust data pipelines
Expertise in prompt engineering, agentic framework design, and LLM pipeline orchestration
Experience deploying LLMs using Triton Inference Server, vLLM, TGI, or ONNX
Good written and spoken English

Nice to have:

Experience with Pinecone, Weaviate, Milvus, or Chroma
Advanced quantization (GGUF, AWQ, EXL2), pruning, and knowledge distillation
Experience with LangChain, LlamaIndex, or AutoGen
Basic understanding of web/client-server architecture and streaming API responses (Asyncio, aiohttp)
Familiarity with RAGAS, DeepEval, or G-Eval
Experience using Docker, Kubernetes, and cloud GPU orchestration (Run:ai, Lambda Labs)
Knowledge of C++, Triton, or CUDA for custom kernel development

Obowiązki

Design and implement advanced methods in prompt orchestration, fine-tuning (SFT/RLHF/DPO), and autonomous agentic workflows
Curate high-quality training data from large-scale text and multi-modal sources
Identify patterns in model hallucinations and visualize evaluation metrics
Tune hyperparameters and improve inference speed/accuracy through PEFT (LoRA/QLoRA) and advanced prompt engineering
Collaborate with Product and Data Engineering teams to integrate LLM features
Track and report progress using benchmarks (MMLU, HumanEval) and internal KPIs
Stay updated on new techniques (e.g., State Space Models, Transformer variants) and evaluate for production readiness
Mentor junior colleagues to enhance team expertise

Benefity

Equal opportunities environment with transparent and value-based corporate culture
Competitive salary packages with performance-based annual reviews
Employment via Contract of Employment (UoP) aligned with Polish Labour Law
Guaranteed paid vacation, public holidays, and medical leaves as per statutory regulations
Continuous growth and development through internal knowledge hubs, corporate courses, and free English classes
Comprehensive private medical insurance supplementing standard NFZ coverage

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Inne informacje

Please be informed that the data controller is SQUAD POLAND Sp. z o.o. ("controller"). You have rights regarding your personal data including access, rectification, erasure, restriction, objection, portability, and complaint to supervisory authority. Data processing is for recruitment purposes. Provision of mandatory data is required by law; refusal may prevent recruitment. Data processed until recruitment completion or consent withdrawal. Data recipients include Just Join IT and other entities involved in recruitment processing.

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