Senior AI Engineer

DRIMCO GmbH; München; Vor Ort; EUR 90.000 - 140.000; Vollzeit

Benefits dieser Stelle

Remote work not specified

Zusammenfassung

DRIMCO GmbH in Munich is seeking a seasoned AI/ML engineer to build, deploy, and scale production AI systems. You will own end-to-end ML pipelines from data ingestion to monitoring, ensuring robust, scalable solutions across the stack.

Ideal candidates have 3+ years in ML, strong Python/PyTorch, MLflow, and Docker/Kubernetes experience, plus cloud familiarity (AWS/GCP/Azure) and a startup mindset. You will collaborate with founders and product teams to ship impactful AI features.

Qualifikationen

• 3+ years of experience building and running production AI/ML systems.
• Strong CS background with NLP/CV understanding.
• Hands-on Python, PyTorch, SQL, graph databases, load balancing experience.
• Experience tracking experiments with MLflow.
• Understanding of AI foundations, LLMs and model internals.
• Deploying AI systems with Docker, docker-compose and Kubernetes.
• Familiar with ML CI/CD, model monitoring and versioning.
• Knowledge of GenAI approaches (RAG).
• Experience scaling ML systems in production.
• Cloud experience (AWS, GCP, Azure).
• Startup/product-driven environment experience.
• End-to-end ownership of AI features in production-grade.
• Experience with MCP/A2A protocol and agentic frameworks a plus.
• DevOps experience a plus.
• ETL process experience a plus.

Aufgaben

• 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.

Kenntnisse

ML systems experience

MLOps mindset

Cloud platforms

Python

PyTorch

SQL

MLflow

Tools

Docker

docker-compose

Kubernetes

Graph databases

AWS

GCP

Azure

CI/CD for ML

Jobbeschreibung

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 end-to-end production-grade.
• Experience with MCP / A2A protocol and agentic frameworks is a plus.
• DevOps experience is a plus.
• Experience with the ETL process is a plus.