Senior Software Engineer, Flood Risk
ICEYE is hiring a Senior Software Engineer, Flood Risk. Level rates it ; you can apply on ICEYE.
Level's read on this job
- Level rates this software engineer role Little AI ●○○○: aI is not part of the work.
- The posting allows some remote work.
- Tools and skills the posting cites include MLflow, SageMaker and MLOps.
- Level lists 198 other open roles at ICEYE.
- The role was posted in the last few days.
AI in this role
Role highlights
Senior Software Engineer, Flood Risk
Location: Espoo, Finland (relocation supported)
Team: Flood Risk, Flood Solutions
Reports to: Flood Risk Team Lead
Workplace model: Hybrid (minimum 3 days per week in the office)
Employment is subject to applicable security screening (incl. SUPO, where required)
Why this role matters
We are looking for a Senior Software Engineer to turn ICEYE's flood observation history into data products that help customers understand flood risk at their locations and areas of interest.
ICEYE has observed floods worldwide with its synthetic aperture radar (SAR) satellite constellation for years, so we know where water has gone, how deep it got, and how often it returns. We are turning our analysis catalog into predictive insights and building a product that gives customers near real-time understanding of flood risk for a location of interest.
You will join a senior team where the data scientists and machine learning engineers build the flood models, and you make them work in production, 24/7.
Your day-to-day responsibilities
You will own how flood risk gets from our models and data into customers' hands. In practice, that means:
Design and build the services and pipelines that compute, store, and serve flood risk for any location or area of interest.
Take models from notebooks to production with the data scientist and the ML engineer: tested, versioned code; reproducible inference; staged rollouts; and drift monitoring. A big part of the job is deciding what gets pre-computed and what runs at request time.
Design API-first. The contract is agreed before the code; the OpenAPI specification is the source of truth, and the documentation (reference, examples, changelog) lives in the repository as code, reviewed and validated in CI like everything else.
Build security and privacy in as a day 0 item: authentication, authorization, tenant isolation, least privilege, data minimization, and audit trails, so we can reproduce and explain every response we have served. You take part in threat modeling.
Run what you build, with automated tests and deployments, SLOs, dashboards and alerts, and automating away toil. This role includes an on-call rotation.
Design for data at scale (years of observations, customer portfolios of any size): data models, storage formats, partitioning and the batch versus streaming trade-offs, watching cost per request as closely as latency.
Make architecture decisions with our Staff Engineers (they work across the teams) and write them down as lightweight ADRs.
Mentor teammates and help the data and ML colleagues with production engineering practices (they will teach you flood science in return).
What we are looking for
Must have
5+ years building and running production software in the cloud (AWS, Kubernetes, Docker), owning design and delivery at senior level.
You have operationalized machine learning models: taken research or notebook code into a production service or batch pipeline, and kept it versioned, reproducible, and monitored after launch.
You have architected and built API-first products for external customers, and evolved them without breaking callers (versioning, error contracts, backward compatibility).
API documentation as code is normal for you: OpenAPI with real examples, generated references, docs checked in CI.
You design with security and privacy as the default, backed by practical experience in OAuth 2.0 and OIDC, authorization models, the OWASP API Security Top 10, and protecting customer data.
You have operated software 24/7; high automation, test automation, and observability (metrics, logs, tracing, SLOs, alerting) are what you live and breathe, and you have learned from real incidents.
Experience designing data-intensive applications: data modeling, storage formats, partitioning, and performance and cost at scale.
Deep proficiency in Python for production services and data processing, and you are comfortable reading (and refactoring) a data scientist's notebook.
Good communication; you can explain a technical trade-off to an engineer, a data scientist, a product person, or a customer, and you are comfortable shaping a product while it is still being defined.
Hands-on use of AI coding assistants and agents in your daily work, with judgment on where they help and where they do not.
Nice to have
Go for the services where raw performance matters.
MLOps and model serving tooling (MLflow, ONNX, SageMaker, feature stores and the like).
Geospatial data at scale: rasters, xarray, rasterio, GDAL, PostGIS, Cloud Optimized GeoTIFF, Zarr.
Insurance, catastrophe modeling, or flood risk; knowing what an insurer does with a risk score at quote time helps a lot.
ISO 27001, SOC 2, DORA, or GDPR in a regulated data environment, including customer security reviews.
Terraform.
Application process
Talent Acquisition Partner screening
Director interview
Live Coding and Whiteboarding
SVP interview
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 Software Engineer, Flood Risk at ICEYE rates 21 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● 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. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- Typical software engineer job
- $167k
This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs
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 how you've used MLflow in your day-to-day work.
- What are the limits of SageMaker that you've run into, and how did you work around them?
Adapt your resume
- List these exact terms on your resume: ML Ops, MLflow, and SageMaker. 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.
Get your CV reviewed before you apply
Send your CV and the role you want next. Your review arrives by email within 3 days.
Get new remote software engineer jobs by email
One email a week, each job rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free.
Similar roles
Software Engineering roles that involve little AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step