Senior ML Engineer – 3 Month Project

🔥 25 minutes ago

🇩🇪 Germany – Remote

⏳ Contract/Temporary

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 15%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Intetics

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1995

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Intetics is an innovative company providing custom software development services, specializing in AI and machine learning solutions. They offer Remote In-Sourcing® to build expert teams for software engineering and data processing projects, along with advanced tools like TETRA™ for software quality assessment. Intetics aims to empower businesses by leveraging high-quality data and integrating modern technologies across various industries, including healthcare, finance, and more.

📋 Description

• Build and orchestrate ML pipelines using Kubeflow Pipelines (KFP v2) • Train ML models on GPUs and manage GPU resources within Kubernetes • Fine-tune transformers and LLMs • Track experiments and models using MLflow • Build classical ML models with XGBoost and CatBoost • Process large datasets using SQL Server and DuckDB • Develop Python-based pipelines, integrations and tooling • Maintain engineering standards through testing, clean code and CI/CD with GitLab CI • Work in a secure, zero-trust / secure-by-default environment with network policies and restrictive container permissions

🎯 Requirements

• Hands-on experience with Kubeflow Pipelines, ideally KFP v2 • Experience training models on GPUs • Practical experience with LLM / transformer fine-tuning • Experience with MLflow • Strong knowledge of XGBoost, CatBoost or similar boosting models • Strong Python engineering skills • Solid SQL experience and understanding of large-scale data processing • Experience with CI/CD, clean code and automated testing • Production-grade ML/MLOps experience beyond notebook-based experimentation • Experience working in enterprise or regulated cloud-native environments • German proficiency at B2+ level • English proficiency at B1+ level