Senior Machine Learning Engineer (FinTech / MLOps / Agentic AI)

Summary: Design, develop, and deploy machine learning models for credit scoring and merchant underwriting within a FinTech environment. The role involves building agentic AI workflows, implementing MLOps processes, and ensuring regulatory compliance while collaborating with data engineering teams.

Hello,
We are called People More because we treat our employees with respect, but also because the projects we work on are for people and should be easy and pleasant to use. We are technological, but we look at the bigger picture :)
The company is made up of people with a huge client base in the country and abroad, for whom we build projects from scratch (UX, UI, frontend, backend, mobile) or in part. We work directly for our clients and also support our partners in their own solutions. This ensures a wide range of projects and the ability to change! We work with clients all over the world.
For the project that we are working on with our partner, we are looking for Senior Machine Learning Engineer (FinTech / MLOps / Agentic AI).

Your duties will include:

• Designing, developing, and deploying machine learning models for credit scoring and merchant underwriting, covering the entire ML lifecycle.
• Building point-in-time-correct features using a shared feature store to support BNPL (Buy Now, Pay Later) and MCA (Merchant Cash Advance) decisioning.
• Cooperating with Data Engineering teams to establish data source contracts, quality requirements, and data freshness SLAs.
• Designing and maintaining agentic workflows, including agent loops, orchestration graphs, context management, tool integrations, evaluation mechanisms, and guardrails.
• Implementing MLOps processes, including model versioning, automated CI/CD pipelines, and champion/challenger or shadow deployment strategies.
• Monitoring production models for data drift, population stability, and performance degradation, and implementing retraining, recalibration, or rollback mechanisms.
• Ensuring model explainability and regulatory compliance through appropriate documentation, validation evidence, and explainability techniques.
• Supporting regulatory and audit requirements, including CCD2 creditworthiness assessment.
• Developing automated validation and backtesting frameworks integrated with the MLOps pipeline.
• Building and maintaining automated experimentation, evaluation, retraining, and model promotion workflows.
• Optimizing the reliability, observability, and operational costs of ML and agentic AI systems

Requirements that must be met:

• Strong commercial experience in Machine Learning Engineering, including building and operating ML solutions in production environments.
• Hands-on experience across the full ML lifecycle: feature engineering, model training, validation, deployment, and monitoring.
• Very good knowledge of Python and SQL.
• Practical experience with Spark and/or Databricks in large-scale machine learning environments.
• Strong understanding of model validation techniques, including backtesting, Population Stability Index (PSI), Gini/KS metrics, and model calibration.
• Experience with MLOps, including model registries, versioning, CI/CD pipelines, model monitoring, drift detection, and automated alerting.
• Knowledge of champion/challenger testing and shadow deployment strategies.
• Practical experience with feature stores and point-in-time-correct feature engineering.
• Familiarity with model explainability methods such as SHAP and LIME, as well as preparing technical and validation documentation.
• Experience in developing advanced agentic AI workflows, including agent orchestration, loop and graph design, context management, tool integration, guardrails, and evaluation frameworks.
• Good understanding of Large Language Models (LLMs) and their practical application in engineering workflows.
• Ability to design and deliver reliable, observable, and cost-efficient ML systems.
• Strong analytical skills, independence, and a hands-on approach to problem-solving.
• Ability to collaborate effectively with engineering, data, and business teams.
• Very good English and Polish

What we offer:

• We are open and honest and we solve problems instead of generating them.
• Maybe it’s obvious, but we really respect our employees and associates. We used to be software developers, too, and we appreciate that job!
• A small team
• An international working environment and international projects
• Private medical care
• Sports card
• Training courses
• Hybrid working model: preferably 1 day per week in the Warsaw or Cracow office.

Why it’s a good idea to work with People More?

• If you are not satisfied with your work or your tasks, we’ll find a way out together!
• If you get bored, we will offer you a new product and new, fascinating tasks
• We will work on your brand together: you will get an opportunity to attend conferences, including as a speaker, and we will help you publish in recognized magazines and online
• We will facilitate your access to challenges that are usually difficult to get
• At any time, you can talk directly to the board of People More—we talk your language because the company’s founders are software developers and designers!

What does the recruitment process look like?

• A friendly remote initial interview
• A remote technical talk
• The decision to work together!

### Salary

120 - 170 zł/h

### contract

B2B

### Location

Kraków /Warsaw / hybrid