Senior Python

2 дней назад

Украина, Украина N-Cube Полный рабочий день

We are looking for a highly skilled Senior Python / AI Workflow Engineer to help build the next generation of ecological AI infrastructure. You'll join a team transitioning from scientific research to production systems, working on a modular AI workflow for acoustic detection — a critical component that supports biodiversity protection and regulatory compliance across Dutch municipalities.

You will take a research-grade AI workflow (from a scientific article) and turn it into clean, maintainable, modular Python code that can scale, run reliably in Docker, and integrate into future MLOps pipelines. This role is ideal for a senior engineer who thrives at the intersection of research and production engineering, enjoys structuring complex workflows, and wants to contribute to meaningful environmental impact.

Requirements

  • 5–8+ years of professional experience with Python (production-level, modular codebases)
  • Strong background in scientific computing (NumPy) and deep learning frameworks (PyTorch or TensorFlow)
  • Proven ability to translate research code or academic workflows into production-ready systems
  • Experience with data preprocessing, feature extraction, and model training/evaluation pipelines
  • Knowledge of data versioning approaches (Git-LFS or similar tools)
  • Expertise with Docker for ML workloads (image building, reproducibility, runtime optimization)
  • Familiarity with MLOps tools such as MLFlow, Weights & Biases, or similar experiment-tracking systems
  • Strong understanding of configuration-driven architecture and modular workflow design
  • Excellent English communication skills (Upper-Intermediate+)

Responsibilities

  • Reproduce an AI workflow described in a scientific research paper using clean, production-oriented Python
  • Implement modular components for preprocessing, feature extraction, model training, inference, and evaluation
  • Develop modular, testable, configuration-driven code prepared for pipeline automation
  • Prepare all components for MLOps integration (logging, experiment tracking, artifacts, metrics)
  • Contribute to the transition from prototype to scalable deployment across multiple municipalities

We offer:

  • Paid vacation (up to 20 working days)
  • Paid sick leaves (10 working days)
  • National holidays as paid time off
  • Flexible working schedule and full remote work format
  • Direct collaboration with the client's engineering and AI teams
  • Engaging, meaningful projects with real ecological impact
  • Opportunity to work with cutting-edge AI technologies and large-scale data systems
  • Regular online teambuildings and strong team culture

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