Staff ML/AI Data Engineer

Reposted 3 Days Ago
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Hiring Remotely in Germany
Remote
Senior level
Cloud • Information Technology • Internet of Things
The Role
The Staff ML/AI Data Engineer will develop scalable data infrastructure, create MLOps capabilities, enable real-time data insights, and innovate AI data stacks while collaborating with cross-functional teams to drive data-driven solutions and enhancements for the IoT connectivity platform.
Summary Generated by Built In

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. 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).

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.
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The Company
HQ: Berlin
188 Employees
On-site Workplace
Year Founded: 2014

What We Do

emnify is the leading cloud building block for cellular communications in the IoT stack, connecting millions of IoT devices globally – from electric vehicles to energy meters, alarm systems to GPS trackers, thermometers to health wearables.

The emnify API and SIM technology connect and secure any kind of IoT deployment to its application back-end. emnify’s cloud-native integrations and no-code workflows ensure seamless lifecycle scalability for deployments of all sizes – from local start-up to global enterprise.

The emnify IoT SuperNetwork is the largest globally distributed mobile cloud core network of its kind, supporting local network access (2G – 5G, LTE-M, NB-IoT) in over 180 countries from more than 25 cloud regions – and counting. emnify’s solution is built on partnerships with the leading hyperscaler cloud service providers, system integrators and hundreds of radio network operators worldwide.

Founded in 2014, emnify was the first to transform cellular IoT connectivity into an easy-to-consume cloud resource – trusted today by thousands of the world’s most innovative companies. To learn more about emnify, please visit www.emnify.com

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