Senior Data Scientist BN_28/10/2026

180 - 200 PLN/ godz./ godz.

SeniorHybryda·WarszawaFull-time

#469171·Dodano wczoraj·0

Źródło: Margo

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Tech Stack / Keywords

Python FastAPI LangGraphGoogle ADKDSPyvLLMJenkinsArize PhoenixKubernetes pytest

Podsumowanie oferty

Develop LLM-based agentic solutions to automate business processes for the Investment Banking division, within a team developing and industrializing applications. The role focuses on AI agents, data extraction and deploying models, using technologies including Python, FastAPI, LangGraph and Google ADK.

Wymagania

Strong Python skills and extensive experience in Object-Oriented Programming and enterprise software design patterns.
Proven track record building asynchronous microservices and endpoints using FastAPI.
Hands-on practice with pytest for unit, functional, and integration testing of ML/LLM pipelines.
Use Bash scripts for automation, data handling, and container interaction.
Understanding of LLM architecture, demonstrated through a project portfolio.
Experience architecting multi-step, stateful agentic graphs using LangGraph or Google ADK.
Hands-on experience optimizing LLM pipelines programmatically using DSPy.
Practical knowledge of deploying and running high-throughput open-weight models on GPU infrastructure using runtimes such as vLLM.
Hands-on familiarity with automated build, test, and release pipelines using Jenkins.
Experience setting up tracing, drift detection, and automated evaluations for generative workflows using tools such as Arize Phoenix.
Dedication to shipping stable, secure code into banking infrastructure where compliance, auditability, and data security are essential.
Experience with Kubernetes.

Nice to have:

Experience with CUDA and fine-tuning.

Obowiązki

Design and develop LLM-based agentic solutions to automate complex business processes.
Work closely with business teams to identify needs and drive the adoption of AI solutions.
Develop data extraction pipelines and implement evaluation and observability frameworks for AI agents.
Deploy and industrialize models (LLMs, GPUs), ensuring quality through testing and DevOps best practices.
Take full ownership in driving AI features.
Respect the boundaries and non-deterministic nature of LLMs, communicate constraints clearly, and build robust safety rails.
Communicate technical trade-offs with architects and business users, and mentor peers.
Test ideas and PoCs quickly, validate feasibility with data, and avoid technical debt.

Benefity

Build expertise in agentic AI architectures and the industrialization of LLMs in production.
Work on high-visibility projects within the Investment Banking division.

Margo

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