Data Scientist - MID Profile - BN 12/11/26 MARGO
Projets IT complexes avec management et développement des talents.
CDI
Warszawa
Télétravail fréquent
Salaire : non spécifié
Les compétences que l’on cherche
Communication
IA générative
FastAPI
CUDA
Kubernetes
+6
Votre nouvelle entreprise
400 collaborateurs
Software
IT / Digital
Âge moyen : 30
Créée en 2005
Chiffre d'affaires : 42M€
Chez MARGO, nous croyons que la complexité est une opportunité. C’est pourquoi nous menons exclusivement des projets à haute complexité IT.
Pour accompagner nos consultants dans ces environnements exigeants, nous avons créé le Pôle EXCELLENCE, 100% dédié au management et au développement des talents.
Chaque consultant est rattaché à une Practice, pilotée par un Practice Manager (un expert issu du terrain).
La mission principale du PM est de faire grandir les compétences de sa Practice : suivi de carrière, accompagnement projet, formations certifiantes, plan d’évolution…
Concrètement, cela veut dire que :
vous progressez en continu sur des missions stratégiques et complexes ;
vous bénéficiez d’un encadrement de proximité et de l’expérience d’experts métiers ;
vous boostez votre employabilité en collaborant avec des clients de référence.
Notre promesse : du sur-mesure, au service de votre ambition et à la hauteur de votre talent.
Vos missions au quotidien
Context:
A team responsible for the development and industrialization of applications for the Investment Banking division. Accelerating the integration of generative AI solutions and AI agents into business processes. A strategic environment within the platform, with high-impact use cases in document analysis, credit, and finance.
Expectations:
- Strong Python with extensive experience in Object-Oriented Programming and enterprise software design patterns.
- Proven track record building asynchronous microservices and endpoints using FastAPI.
- Hands-on practice in pytest (unit, functional, and integration testing for ML/LLM pipelines).
- Bash scripts for automation, data handling, and container interaction.
- LLMs Architecture understanding proven by project portfolio.
- 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 (experience with CUDA and fine-tuning is a strong plus).
- Hands-on familiarity with automated build, test, and release pipelines (Jenkins).
- Experience setting up tracing, drift detection, and automated evaluations for generative workflows using tools like Phoenix Arize.
- Dedication to shipping stable, secure code into flagship banking infrastructure where compliance, auditability, and data security are non-negotiable.
- General Stack: Google ADK, LangGraph, DSPy, vLLM, FastAPI, Python, Pytest. Arize Phoenix. Kubernetes, Jenkins, GPUs.
Responsibilities:
- 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
- You are taking full ownership in driving AI features.
- You remember to respect the boundaries and non-deterministic nature of LLMs, communicate constraints clearly, and build robust safety rails.
- You are a team player, communicate technical trade-offs cleanly with architects and business users, and enjoy mentoring peers.
- You are testing ideas and PoCs quickly, validate feasibility with data and avoid technical debt.
Career Prospects:
- Build expertise in Agentic AI architectures and the industrialization of LLMs in production. Work on high-visibility projects within the Investment Banking division.
