ML Engineer

DRIMCO GmbH; München; Hybrid; EUR 90,000 - 130,000; Full time

Job summary

DRIMCO GmbH in Munich is seeking a Senior ML Engineer to build and operate production AI systems. You will own end-to-end ML pipelines, from data ingestion to deployment and monitoring, partnering with founders and product teams to ship AI features.

You should have 3+ years of hands-on ML experience, strong CS background, and proficiency with Python, PyTorch, and cloud infrastructure. Join a fast-paced startup environment optimizing models at scale.

Qualifications

• 3+ years of experience building production AI/ML systems.
• Strong CS background with NLP/Computer Vision knowledge.
• Hands-on Python, PyTorch, SQL, and graph databases.
• Experience tracking experiments and models with MLflow.
• Solid understanding of AI fundamentals, LLMs, and model internals.
• Deployment experience with Docker, Docker Compose, and Kubernetes.
• Familiar with model monitoring, versioning, and ML CI/CD.
• Experience with (Gen)AI approaches and RAG.
• 3+ years of ML work experience.
• 3+ years of Python experience.
• 1+ years of AI Agents experience is a plus.
• Experience scaling ML systems in production.
• Strong MLOps mindset.
• Cloud exposure (AWS, GCP, Azure).
• Startup/product-driven background.
• Ownership of AI features end-to-end.
• MCP/A2A protocol or agentic frameworks a plus.
• DevOps experience is a plus.
• ETL process exposure a plus.

Responsibilities

• Build, deploy, and maintain production AI systems.
• Own end-to-end ML pipelines: data ingestion, training, validation, deployment, monitoring.
• Optimize models for performance, scalability, and reliability.
• Collaborate with founders, engineering, and product teams to ship AI features.
• Monitor live models, retraining, and improve model quality over time.
• Improve MLOps and deployment infrastructure.

Skills

Python

PyTorch

Machine Learning

NLP

Computer Vision

SQL

Graph Databases

Experiment Tracking

ML Ops

Cloud Platforms

AWS

GCP

Azure

CI/CD for ML

Docker

Kubernetes

DevOps

ETL

Tools

Docker

Docker Compose

Kubernetes

MLflow

CI/CD

Graph Databases

Job description

Responsibilities:

• Build, deploy, and maintain production AI systems.
• Take ownership of end-to-end ML pipelines (data ingestion, training, validation, deployment, monitoring).
• Optimize models for performance, scalability, and reliability.
• Work closely with founders, engineering, and product teams to ship AI features.
• Monitor live models, handle retraining, and improve model quality over time.
• Improve our MLOps and deployment infrastructure.

Requirements:

• 3+ years of experience building and running production AI / ML systems.
• Strong Computer Science background and understanding in Natural Language Processing / Computer Vision.
• Solid hands-on experience with Python, PyTorch, SQL, graph databases, load balancing, etc.
• Experience tracking experiments and models using, e. g., MLflow.
• Strong understanding of AI foundations, LLMs, and model internals.
• Practical experience deploying AI systems using Docker, Docker Compose, and Kubernetes.
• Familiarity with model monitoring, versioning, and CI/CD for ML.
• Deep understanding and practical experience of basic (Gen)AI approaches, e. g., RAG.
• Practical experience with a multi-agent AI system is a plus.
• 3+ years of work experience with Machine Learning.
• 3+ years of work experience with Python (Programming Language).
• 1+ years of work experience with AI Agents.
• Experience scaling ML systems in production.
• Strong MLOps mindset.
• Cloud infrastructure experience (AWS, GCP, Azure).
• Experience in a startup or product-driven environment.
• Experience owning AI features in end-to-end production-grade environments.
• Experience with MCP / A2A protocol and agentic frameworks is a plus.
• DevOps experience is a plus.
• Experience with the ETL process is a plus.