Senior MLOps Engineer, ISR
ICEYE is hiring a Senior MLOps Engineer, ISR for a remote role open to applicants in Germany. Level rates it ; you can apply on Level.
AI in this role
Senior MLOps Engineer building sustainable infrastructure, pipelines, and deployment practices for defense AI models.
Role highlights:
Senior MLOps Engineer, ISR
Location: Berlin, Germany
Department: ISR Analytics
Reports to: VP of ISR Analytics
Employment type: Permanent
Workplace model: Hybrid
Employment is subject to applicable security screening (incl. SUPO, where required)
Why this role matters:
ICEYE's Intelligence, Surveillance and Reconnaissance (ISR) AI team builds models that turn satellite imagery into intelligence for defense customers. Your job is to work with data scientists to build sustainable infrastructure, workflows, and deployment practices for the AI models, both in the cloud and for on-premise systems. You sit with the AI team and work with them to build the infrastructure they train, evaluate and ship on. Like our platform work, every environment is temporary and must be reproducible from code; a model is only done when it runs, monitored, on hardware we don't control.
Who We Are
ICEYE is the world leader in sovereign intelligence from space. We deliver persistent monitoring capabilities to detect and respond to changes in any location on Earth.
ICEYE owns the world's largest and most advanced SAR (synthetic aperture radar) satellite constellation. To our customers we provide intelligence with unmatched quality, latency and revisit times, in any weather, day or night. To governments who choose to operate their own constellation we provide this proven capability as a sovereign system.
ICEYE-built constellations serve customers in defence and intelligence, environmental monitoring, insurance and emergency management. We enable fast decisions that contribute to a safer future.
Founded and headquartered in Finland, ICEYE operates globally with over 1000 employees across Europe, North America, the Middle East, and Asia-Pacific.
Your day-to-day responsibilities
Build training, evaluation and packaging pipelines that take a model from experiment to versioned, deployable release.
Deploy and serve models on Kubernetes with GPUs, in the cloud and on-prem, including air-gapped sites.
Package models, weights and dependencies so they install and upgrade offline.
Manage GPU compute: scheduling, drivers, utilization and cost, across cloud and on-prem hardware.
Track data, experiments and model lineage, so any result can be reproduced and audited.
Monitor models in production for performance, drift and failures, without relying on outside connectivity.
Write tooling in Python that the AI team uses every day, and work in the model codebase alongside them.
What we’re looking for
Must haves:
Senior hands-on engineer (not an engineering manager or architect role).
Proven experience deploying ML models to production and running them there, not only training them.
Strong Python, and comfort reading and changing ML code (PyTorch or similar).
Hands-on Kubernetes and containers, including GPU workloads.
Infrastructure as code and CI/CD for ML (for example Terraform, Helm, GitHub Actions).
Daily use of AI tools in engineering work, beyond chat: generating and reviewing code, configuration and tests.
High autonomy: you find problems, propose fixes and drive them through.
Motivation to work in new defense: building technology used by defense forces.
Nice to haves:
Deployed models to on-prem, edge or air-gapped environments.
Model serving and optimization: Triton, TorchServe, KServe, ONNX, TensorRT, quantization.
Computer vision or geospatial data (satellite, SAR, raster, PostGIS).
ML pipeline and tracking tools such as MLflow, Kubeflow, Argo Workflows, DVC or Weights & Biases.
Large-scale data processing for imagery (Dask, Ray, Spark, object storage).
Strong IC track record in a startup or a fast-changing company launching new products.
Clear communicator who works well with researchers and experienced engineers.
Application Process
Outline the stages of this role, including task stages.
Working at ICEYE
At ICEYE, you’ll join a diverse and highly engaged team united by the ambition to make the impossible possible. As a global scale-up, we combine speed and ambition with the opportunity to take real ownership from day one. Your growth, wellbeing, and success are a priority, with continuous professional development, training opportunities, and a culture where collaboration is how we win.
How We Work (Our Values)
Make the impossible possible: We set ambitious goals and stay calm under pressure. We bring grit, optimism, and ownership when things get hard, and we keep moving until we find a way.
Be curious: Go deep, ask questions, listen carefully, and think critically. Understand the “why” behind decisions.
See the big picture: Stay close to what’s happening across the company so you can make better decisions. Consider how your work affects others.
Drive effective teamwork: Create psychological safety, invite different perspectives, and build inclusive teams. There are no bad questions.
Act as one team: We win together. We match tasks to the right owner and stay agile as priorities shift.
Have fun: What we do matters—and it should be enjoyable. Celebrate progress, take pride in results, and share the wins.
Benefits
Our benefits are designed to support your health and wellbeing, at work and beyond. We keep improving them based on employee feedback, and offerings vary by location. Talent Acquisition will confirm what applies for this role and location during the process.
Our Commitment to Diversity, Equity, and Inclusion
We want ICEYE to be a place where people can be themselves and do great work. Different backgrounds and perspectives make us stronger, which is why we work to create an environment where people feel included, respected, and able to speak up. Whatever your background, we want you to bring your authentic self to the table.
We’re committed to fair, inclusive hiring and equal opportunity. Everyone is welcome to apply. If you need any adjustments or support during the recruitment process, tell us—we’ll do our best to help.
Apply now to start your ICEYE journey, and help us continue to make the impossible possible together. Read more about ICEYE and working with us at iceye.com.
How we rate this
Senior MLOps Engineer, ISR at ICEYE rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- Tell me about a project where mlops was part of your work. What did you do?
- Tell me about a project where infrastructure was part of your work. What did you do?
- Tell me about a project where model deployment was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: ML Ops, Computer vision, MLOps, Infrastructure, and Model Deployment. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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