Machine Learning Engineer (m/f/d) 

Salary: €75.000 to €130.000 gross per year (depending on experience and seniority)
Location: Remote (Germany)

About the Role

In this role, you will take a central position in building production-ready AI systems within an innovation-driven environment.

Your focus is on developing and validating new machine learning initiatives end to end, from early prototypes to adoption-ready solutions. You will design and implement scalable systems that process complex data streams across text, speech, and image, while ensuring they meet real-world requirements in terms of performance, reliability, and deployment constraints.

Working at the intersection of machine learning, data engineering, and product, you will build end-to-end solutions that connect data ingestion, model inference, and user-facing applications. Your work enables teams to bring new AI capabilities into production, including in highly constrained environments such as on-premise and air-gapped systems.

Your Responsibilities

• Build end-to-end ML prototype systems from data ingestion to inference and product integration (e.g. search, insights, UX flows)
• Develop and deploy machine learning models in production-like environments
• Design and implement scalable inference pipelines (e.g. Triton or TorchServe)
• Create evaluation frameworks including datasets, baselines, and metrics such as quality, latency, and cost
• Provide clear recommendations based on evaluation results
• Package solutions for adoption through containerization, reproducible deployments, and clear documentation
• Implement RAG pipelines using vector databases such as pgvector or Milvus
• Build streaming and real-time analytics pipelines for use cases like video or speech processing
• Optimize models for performance using techniques such as quantization, pruning, or distillation
• Contribute to MLOps processes including monitoring, A/B testing, rollbacks, and lifecycle management
• Ensure operational readiness through proper instrumentation, monitoring, and handling of sensitive data
• Collaborate closely with Data Scientists, Research, Data Engineering, and DevOps teams

What You Bring

• 3 or more years of experience in Machine Learning Engineering or a similar role
• Strong Python skills and hands-on experience with PyTorch and/or TensorFlow
• Proven experience deploying ML models into production (e.g. NLP, ASR, Computer Vision)
• Solid experience with Docker and Kubernetes in production-like environments
• Experience building API-based ML services and CI/CD pipelines
• Strong understanding of performance trade-offs across latency, cost, and scalability
• Experience with evaluation, monitoring, and experiment tracking
• Ability to move models from experimentation to stable, reproducible systems
• Structured and pragmatic working style with strong ownership
• Eligibility to work in Germany and based in Germany 

Nice to Have

• Experience with LLMs and RAG systems
• GPU serving and optimization (e.g. Triton, ONNX, TensorRT, CUDA)
• Experience with streaming or data pipeline tools such as Kafka, Ray, Spark, Flink, or Beam
• Familiarity with MLflow or similar MLOps tools
• Experience in regulated or public-sector environments
• German language skills (B1 or higher)

What You Can Expect

• Work on production-grade AI systems with direct impact
• A modern ML stack including Kubernetes, streaming systems, and hybrid or on-premise deployments
• Exposure to challenging environments such as air-gapped or high-security setups
• High ownership and visibility across multiple teams
• Access to modern GPU infrastructure and tooling
• Opportunity to shape ML and MLOps standards from the ground up
• Remote-first setup within Germany with regular in-person sessions in Berlin
• 30 days of vacation plus equipment and learning budget

You are interested? Feel free to get in touch directly: 
Constantin Clodius 
Phone: +49 170 3660 753 
E-Mail: c.clodius@zabelglobal.com