MARGO

SME-focused bank offering credit management tools

Data Scientist - MID Profile, BN

Applied Machine LearningPosted on Nov 11

Full-timeWarsaw, PolandPLN130 - PLN160 /hrHybrid

About the Job

Requirements

Strong Python skills, with extensive experience in object-oriented programming and enterprise software design patterns.
A proven track record building asynchronous microservices and endpoints using FastAPI.
Hands-on experience with pytest for unit, functional, and integration testing of machine learning and large language model pipelines.
Experience using Bash scripts for automation, data handling, and container interaction.
An understanding of large language model architecture demonstrated through a project portfolio.
Experience architecting multi-step, stateful agentic graphs using LangGraph or Google ADK.
Hands-on experience optimizing large language model pipelines programmatically using DSPy.
Practical knowledge of deploying and running high-throughput open-weight models on GPU infrastructure using runtimes such as vLLM; CUDA and fine-tuning experience are a strong plus.
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.
Ability to ship stable, secure code into banking infrastructure where compliance, auditability, and data security are critical.

Responsibilities

Design and develop large-language-model-based agentic solutions to automate complex business processes.
Work with business teams to identify needs and drive adoption of AI solutions.
Develop data extraction pipelines and implement evaluation and observability frameworks for AI agents.
Deploy and industrialize models, including large language models and GPU-based models, ensuring quality through testing and DevOps best practices.
Take ownership of driving AI features.
Communicate large language model constraints clearly and build robust safety rails that account for their boundaries and non-deterministic nature.
Test ideas and proofs of concept quickly, validate feasibility with data, and avoid technical debt.

Desired Qualifications

Experience with CUDA and fine-tuning.

Salary Range: 130 to 160 (Currency: PLN) (Pay period: per-hour-wage)

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.

About the Company

MARGO

SME-focused bank offering credit management tools

MARGO is a banking partner for small and medium-sized businesses. It provides loans and tools to manage company cash flow. How it works: SMEs access credit options and a digital cash-management platform to handle payments, receipts, and liquidity. The bank focuses on helping leaders grow by offering financing and treasury tools that fit small and mid-sized operations. How it stands out: It is an independent bank dedicated to SMEs, offering tailored financing and cash-management services rather than broad services for all customers, which helps smaller companies manage money more effectively. Goal: To help SME leaders grow their businesses by providing affordable credit and practical cash-management tools.

Company size: 51-200
Company stage: Not listed
Total funding: Not listed
Headquarters: Philadelphia, PA
Founded: 2015

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