Your tasks

Your Role:

At emnify, we are enhancing our capabilities to deliver smarter, more proactive solutions for our IoT connectivity platform. We are looking for a Staff ML/AI Data Engineer to lead this transformation by building scalable infrastructure (data volume per source is growing by hundreds of MB per hour), robust data pipelines, and efficient MLOps workflows. In this high-impact, new role, you will partner with product, data engineers, data scientists and data analysts to enable real-time, predictive insights and drive data-driven innovation.

Your Impact:

• Develop scalable data infrastructure: Lead the design and implementation of real-time data pipelines and ML/AI solutions to advance data maturity across the organization.
• Build MLOps capabilities: Create and maintain machine learning pipelines to support scalable deployment and monitoring of predictive models.
• Enable real-time insights: Build real-time data workflows to deliver low-latency, customer-facing data solutions.
• Innovation : Build an AI data stack to maintain emnify’s competitive edge in the IoT market.
• Collaborate & inspire: Be part of a high-performing team, where you can lead initiatives, share knowledge and grow in a fast-paced, innovative environment.

Your Skills:

• Infrastructure & tooling: Experience developing scalable infrastructures for data analytics, ML and AI.
• MLOps expertise: Proven experience building and automating machine learning pipelines (model deployment, monitoring, optimization).
• Real-time data processing: Strong knowledge of streaming frameworks (e.g., Kafka, Flink, or Spark Streaming) and large-scale real-time databases (e.g., Apache Druid, Clickhouse).
• Cloud-based data platforms : Proficiency with tools like AWS, Databricks, GCP, or similar cloud technologies and data governance frameworks.
• Multi-tenant expertise : Ability to design and scale multi-tenant analytics solutions.
• Programming skills: Expertise in Python, Scala, or Java, with a focus on clean, maintainable code.

Your perks & benefits:

Our flexible work arrangements include monthly in-person workshops, so candidates based in Berlin or nearby cities are preferred.

Location: Berlin, Germany (or remote within the EU, with preference for proximity to Berlin).

• 30 days of vacation
• Learning culture (e.g. German lessons, access to learning experience platform, etc.)
• Mental health support (e.g. access to our mental well-being platform - Plumm)
• Pension Scheme contribution