Description :

Python Developer / Machine Learning Engineer / Lead - Hungary

Experience : 2-12 Years

Location : Hungary (Remote/Hybrid)

About the Role :

We are looking for a Python Developer / Machine Learning Engineer / Lead to design and develop Python-based backend services, automation workflows, machine learning models, and data-driven applications.

This role is open to professionals with 2 to 12 years of experience, and responsibilities span backend development, ML engineering, data pipeline development, optimization, and production deployment.

You will work closely with data engineers, DevOps teams, and product teams to deliver scalable and high-performance solutions.

Responsibilities :

Backend & API Development :

- Develop backend services, APIs, and microservices using Flask, FastAPI, or Django.

- Build automation scripts, schedulers, and utilities for operational workflows.

- Implement business logic, data processing, validation, and integration with databases.

Machine Learning & Model Engineering :

- Build, train, test, and optimize ML models using TensorFlow, PyTorch, or scikit-learn.

- Implement feature engineering, preprocessing, model tuning, and evaluation pipelines.

- Deploy ML models into production using API endpoints, CI/CD workflows, or containerized deployments.

Data Pipeline & Processing :

- Work with data pipelines and distributed processing frameworks using Pandas, NumPy, PySpark.

- Build ETL tasks using Airflow, develop asynchronous tasks using Celery, and ensure smooth data flow across systems.

- Clean, transform, and analyze data for machine learning and backend processing.

Application & Performance Optimization :

- Optimize Python code for speed, memory usage, concurrency, and scalability.

- Improve performance of data processing, ML inference, and backend services.

- Debug, profile, and refactor legacy code and existing pipelines.

Database Management :

- Work with SQL and NoSQL databases including PostgreSQL, MySQL, MongoDB.

- Write optimized queries, schemas, migrations, and indexing strategies.

Deployment, DevOps & Cloud Integration :

- Containerize applications using Docker and orchestrate deployments on Kubernetes.

- Integrate solutions with CI/CD workflows using Git and automated pipelines.

- Collaborate with DevOps teams for environment management and monitoring.

Documentation & Collaboration :

- Create and maintain technical documentation, architecture diagrams, and model reports.

- Collaborate with cross-functional teams including ML, data engineering, DevOps, and product teams.

- Participate in Agile ceremonies, code reviews, and design discussions.

Required Skills :

Python Development :

- Flask, FastAPI, Django

- Python best practices, OOP, asynchronous programming

Data & ML :

- Pandas, NumPy, PySpark

- TensorFlow, PyTorch, scikit-learn

- Understanding of ML lifecycle, model deployment, and MLOps concepts

Databases :

- PostgreSQL

- MySQL

- MongoDB

Workflow & Task Orchestration :

- Airflow

- Celery

DevOps & Cloud Tools :

- Docker

- Kubernetes

- Git

Key Responsibility Areas :

- Deliver high-quality Python services, APIs, and data processing applications.

- Build and maintain ML models and pipelines for scalable production use.

- Develop robust ETL/data workflows and automation tools using Airflow/Celery.

- Ensure strong application performance, efficient coding practices, and optimized data operations.

- Implement CI/CD-ready, containerized applications using Docker + Kubernetes.

- Maintain reliable and well-structured databases across SQL/NoSQL systems.

- Collaborate with cross-functional teams to design and deliver end-to-end solutions.

- Document architecture, pipelines, code logic, and ML workflows clearly.

- Troubleshoot issues, conduct root cause analysis, and deploy fixes promptly.

- Follow best practices in Python development, security, ML engineering, and DevOps

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