Top Machine Learning Jobs in Germany

Design, build, and operate ML platform systems to train, evaluate, deploy, and serve generative models. Improve reliability, scalability, observability, and cost-efficiency of GPU and cloud workloads. Build internal tools and agent-friendly workflows, collaborate with researchers and engineers, and drive platform architecture and automation.

Build and operate ML infrastructure powering model training, evaluation, deployment, inference, observability, and continuous improvement. Improve reliability, scalability, latency, throughput, and cost efficiency. Provide tooling and pipelines enabling fast experimentation, reproducible ML workflows, benchmarking, monitoring, and platform primitives consumable by AI engineers and researchers.

As an AI/ML Engineer, you will develop and optimize machine learning models for mobile apps, collaborating with cross-functional teams to enhance user experiences.

Design, build, and deploy AI systems for early detection of inflammation-related diseases. Lead AI infrastructure, data modeling using medical standards and ontologies, analyze data for strategic decisions, and develop long-term AI roadmaps while ensuring ethical and compliant AI practices.

Own, design, build, and operate distributed, high-load backend services and data pipelines for ML infrastructure. Partner with ML and product teams to deliver self-service, reliable model serving, storage, and deployment components; ensure observability, scalability, and performance while driving technical decisions and continuous improvement.

Build and ship state-of-the-art speech systems end-to-end: model architecture, training (pre-train/fine-tune/post-train), evaluation, tooling, data curation, production inference, and safety/abuse mitigation for voice conversion and related tasks.

Develop and ship features for Junie across CLI and model integrations, experiment with model setups and ensembling for cost-quality tradeoffs, build and test autonomous agent behaviors for long-term maintenance, and own projects from research to production while using Junie daily to iterate on quality and UX.

Design, train, and improve computer-vision and generative ML models; handle end-to-end ML pipeline from data collection to deployment; prototype research ideas and convert successful prototypes into product-ready solutions; optimize models for efficient on-device inference and collaborate with product teams to integrate models.

Design, build, and scale core infrastructure for machine learning models, manage production systems, and implement best practices in MLOps.

The intern will focus on architecting systems for reliable task execution in machine learning agents, implementing verification layers, and optimizing performance.

As a Senior Python Engineer, you'll design and implement scalable solutions, collaborate across teams, and manage infrastructure on cloud platforms, ensuring high-quality deliverables.