Synthetic Data Generation Engineer
Company
NestAI is a European AI lab for defence delivering the adaptive operating system for modern battlefield operations. We develop adaptive intelligence for unmanned and command systems: AI that continuously learns from operational data and adapts to changing conditions.
NestOS is our open, modular and interoperable platform that enables this at scale and keeps capability evolution under sovereign European control. Founded in 2025 by Peter Sarlin, whose previous company Silo AI became Europe's largest AI acquisition, NestAI brings together over 200 engineers and scientists and partners with leading European defence forces and industry.
Role Description
You'll join the synthetic data team inside our ML Platform chapter, the group responsible for generating training data that doesn't exist anywhere else yet. Real-world imagery for object detection in defence contexts is scarce by nature: the situations, assets, and conditions our models need to recognize are rare, hard to capture safely, or simply haven't happened yet. This team builds the generative pipelines that close that gap, generating visual data under controlled conditions for scenarios that are difficult to capture directly. This role is for someone who has trained generative models themselves, not just fine-tuned or called pretrained ones, and who cares as much about whether synthetic data holds up in real-world model performance as about whether it looks convincing.
Day-to-Day Responsibilities:
Since high-quality real-world imagery for our use cases is scarce, this team's job is to generate data that closes the gap without compromising downstream detection performance.
Build and improve generative pipelines that produce synthetic image and video data for object detection models, covering scenarios where real data is scarce or unavailable.
Train and fine-tune diffusion-based generative models, including LoRA fine-tuning, to produce increasingly realistic and varied synthetic data.
Combine generative approaches with other data sources to boost realism and variation and increase variation in the data produced.
Validate synthetic data against real-world outcomes, proving it improves model training, not just that it looks good.
Track the fast-moving generative model landscape and evaluate new open-source models as they emerge.
Work closely with the wider ML Platform chapter and simulation team on shared data infrastructure.
Qualifications:
Several years of hands-on experience training generative models yourself, not only fine-tuning or calling pretrained APIs.
Experience creating synthetic data in domains where real data is limited — image-based fields like medical, hyperspectral, or multispectral imaging are a strong analogue, even outside defence.
Deep familiarity with diffusion models and Python-based ML training frameworks, including LoRA training and the Hugging Face Diffusers library.
Judgment for when synthetic data is realistic enough to actually matter for training, and when it isn't, however good it looks.
Comfortable working with imperfect information in a research area that shifts month to month.
Nice to have:
Experience with Nvidia Omniverse or other simulation environments, and combining simulation output with generative models.
Exposure to generative world models.
Background in a field where generating photorealistic, cost-efficient synthetic scenes at scale mattered (e.g. automotive or gaming).
If your background doesn't match every requirement but the work resonates with you, we'd encourage you to apply. How you think, learn, and take ownership matters more to us than ticking every box.
Why join NestAI
At NestAI, you’ll build meaningful, real-world technology as part of a world-class team of engineers, scientists, and experienced professionals. You’ll work on systems where reliability genuinely matters, contribute to Europe’s security and resilience, and solve problems that demand depth, trust, and craftsmanship.
If you want to build with purpose - and with leading experts in the field - you’ve come to the right place.
What we offer
We offer a growing set of practical benefits to support your work and wellbeing, day to day:
Occupational healthcare (currently provided by Mehiläinen)
Epassi Flex benefit (sports, culture, commuting, wellbeing)
Lunch benefit (25% tax-free coverage)
Regular team lunches and all-hands events
Your choice of Mac or PC
Holiday allowance (50% of holiday salary)
Phone benefit according to company policy (subscription and device)
We are continuously developing and expanding our benefits as we grow.
Practicalities
Employment is subject to applicable security screening (including SUPO, where required).
NestAI is an equal opportunity employer. We consider all applicants based on their skills, experience, and potential.
- Department
- ML Platform
- Locations
- Helsinki, Tampere, Turku
- Remote status
- Hybrid
- Employment type
- Full-time
About NestAI
Physical AI is moving from theory to reality. The systems being built today will shape how societies protect people, operate critical infrastructure, and respond under pressure for decades to come.
At NestAI, close to 200 engineers and scientists work at the intersection of software, hardware, and AI — developing autonomy, sensing, and command capabilities for mission-critical use. This isn’t demo work. It’s real systems, built for real environments.
We build in Europe, with open and interoperable architectures, so that critical capabilities can evolve over time without lock-in — and remain accountable to the societies they serve.