You’ll be working on diverse machine learning projects for local and international companies as well as in academic research. This will involve different phases of the end-to-end delivery – direct contact with the client, business analysis of the problem, coming up with an appropriate solution, implementation and moving it to the production environment. Key Responsibilities ● Design and develop end-to-end agentic AI solutions using modern LLM frameworks ● Build and deploy Generative AI applications using Python ● Develop and manage AI agents, including tool integrations, memory management, and reasoning workflows ● Implement agent orchestration for multi-agent systems and complex task automation ● Apply advanced prompt engineering techniques to optimize model performance ● Establish agent observability frameworks (monitoring, tracing, logging, evaluation, guardrails) ● Deploy AI solutions using container-based architectures (Docker, Kubernetes) ● Ensure scalability, reliability, and security of AI systems in production ● Integrate AI agents with enterprise APIs, databases, and external systems ● Continuously evaluate model performance and implement optimization strategies Required Skills & Qualifications: ● Strong proficiency in Python programming ● Hands-on experience with Generative AI / LLM frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel, etc.) ● Experience building end-to-end agentic solutions ● Practical experience in agent development and orchestration ● Expertise in prompt engineering and LLM optimization ● Experience with container-based deployments (Docker, Kubernetes) ● Experience implementing agent observability (monitoring, tracing, evaluation frameworks) ● Knowledge of REST APIs and backend integration patterns ● Experience deploying AI applications in cloud environments (AWS / Azure / GCP) ● Understanding of RAG architectures, embeddings, vector databases Preferred Qualifications: ● Experience with multi-agent collaboration frameworks ● Experience with evaluation tools (e.g., prompt testing, hallucination detection, guardrails) ● Familiarity with MLOps practices ● Knowledge of distributed systems design ● Experience with real-time AI applications ● Background in machine learning fundamentals ● Communicative English – minimum C1 level It is great if you have: Experience with DevOps / MLOps tools and practices (e.g. Docker, Kubernetes, MLFlow, KubeFlow, DVC) Familiarity with a deep learning framework (Tensorflow, PyTorch) Experience in using additional data science related libraries (e.g. nltk, opencv, scikit-image, gensim, plotly, seaborn, xgboost, lightgbm) Strong general software development skills and knowledge of best practices Algorithmic and code optimization skills Knowledge of a cloud platform and experience in running cloud-based projects (GCP, AWS, Azure) Salary: 20 000 - 30 000 PLN + VAT (B2B) We offer you: Working with the newest machine learning technologies Budget for self-development per year Possibility to contribute to a variety of interesting projects Internal workshops Personal branding (articles, conference speaker, internal workshop leader) Flexible work hours Remote work possibility Chillout room / free beverages / team & company events Friendly atmosphere MultiSport LuxMed
Non-Financial Risk Analytics, Senior Associate
Statestreet
BI Specialist
Biogen
Senior Data Architect - Semantics & Know
Bayer
Sales Coordinator
Foundation
Senior Graphic Designer (Global Marketing)
Ossur
Junior Administration Specialist
Ossur