Machine Learning Engineer

About the Role

We are seeking an experienced Machine Learning Engineer to join our AI-focused company that develops scalable, production-grade machine learning systems. This role involves leading the entire ML lifecycle—starting from prototyping and evaluation to deployment and production—working on complex applications in natural language processing, speech, computer vision, and generative AI. Collaboration with Data Scientists, Data Engineers, and DevOps teams is key to delivering dependable and scalable AI solutions that drive significant business outcomes.

Responsibilities

• Engineer complete machine learning systems from data ingestion through to deployment in production.
• Develop and deploy ML models within production environments.
• Design scalable inference pipelines using modern serving frameworks.
• Create evaluation frameworks incorporating quality, latency, and cost metrics.
• Implement Retrieval-Augmented Generation (RAG) pipelines with vector databases.
• Build real-time and streaming analytics pipelines.
• Optimize models focusing on performance, scalability, and efficient infrastructure use.
• Participate in MLOps activities including monitoring, A/B testing, and lifecycle management.
• Collaborate with cross-functional engineering teams to integrate AI solutions into production workflows.

Requirements

• Minimum of three years' experience in machine learning engineering or similar roles.
• Proficiency in Python, with practical experience in PyTorch and/or TensorFlow frameworks.
• Demonstrated ability to deploy ML models to production.
• Experience with Docker and Kubernetes technologies.
• Competence in developing API-based ML services and continuous integration/continuous deployment (CI/CD) pipelines.
• Strong understanding of MLOps concepts, including monitoring and experiment tracking.
• Capability to build robust, scalable, production-ready machine learning systems.
• Residence in Germany with valid authorization to work.

Preferred Qualifications

• Experience working with Large Language Models (LLMs) and RAG systems.
• Familiarity with Triton, ONNX, TensorRT, or CUDA.
• Knowledge of streaming and processing technologies such as Kafka, Spark, Ray, Flink, or Beam.
• Experience with MLOps tools like MLflow or equivalents.
• Background in regulated or high-security sectors.
• German language proficiency at B1 level or higher.

Compensation and Benefits

• Competitive annual gross salary ranging from €90,000 to €120,000, based on experience.
• Fully remote work opportunity within Germany.
• Involvement in building production-grade AI systems that impact real-world applications.
• Access to a modern machine learning toolset, GPU infrastructure, and advanced technologies.
• High level of ownership and visibility within engineering teams.
• Opportunity to influence and establish ML and MLOps best practices.
• 30 days of paid annual leave alongside a budget for learning and provision of necessary equipment.