AI Engineer
We are looking for a Senior AI Engineer to work on the AI layer behind our intelligence platform, with a focus on multimodal data and structured knowledge.
We operate on text, social media, imagery, geospatial, and time-series data at scale. Much of the AI challenge is turning that data into knowledge: recognising the real-world entities behind it, enriching them with context, and connecting them so analysts and AI systems can reason across sources, locations, and time.
You’ll bring hands-on experience applying ML and NLP models to real-world data, modelling what they extract into knowledge graphs, and integrating your models into large-scale data pipelines. You’ll also adapt models through fine-tuning where off-the-shelf ones fall short. We care more about how you reason through model and architecture choices than about any specific framework.
This is a hands-on, senior role with real ownership over models, pipelines, and technical direction. It is an engineering role, not a research one: you’ll own models end-to-end, from fine-tuning to serving them on-prem and running them in production.
Requirements
Engineering Skills:
- Strong Python skills and experience shipping production AI/ML services.
- Experience with FastAPI, Docker, and asynchronous programming.
- Good knowledge of databases, including PostgreSQL, Elasticsearch, and vector databases.
- Proven experience operating and integrating AI workloads into queue-based, distributed data pipelines (e.g. Celery, RabbitMQ, Apache Kafka, or cloud equivalents) for large-scale AI enrichment and batch inference.
AI Skills:
- 3+ years of hands-on experience in AI/ML, with a focus on LLM-based systems in production.
- Proven experience with information extraction from unstructured data, including entity and relation extraction, entity resolution, or entity linking.
- Experience with knowledge graphs, from designing ontologies and graph schemas to working with graph databases (e.g. Neo4j) or GraphRAG.
- Hands-on experience with multimodal models applied to real-world data.
- Practical experience fine-tuning open models (e.g. LoRA/PEFT, SFT, embedding models), including dataset preparation and evaluation.
- Strong understanding of transformer architectures and deep learning frameworks such as PyTorch.
- Understanding of evaluation methodologies for model outputs.
- Upper-intermediate (B2) English or higher.
Nice to Have
- Experience with geospatial data, satellite or aerial imagery, remote sensing, or geospatial computer vision.
- Experience with on-prem model serving and inference optimisation (vLLM, TGI, quantisation).
- Background in threat intelligence, OSINT, geospatial intelligence, or defence.
We Offer:
- Opportunity to contribute to a mission-driven startup and support prestigious clients, including governments worldwide, enterprise clients, and leading NGOs in tackling global security challenges.
- Autonomy and freedom to drive experiments and bring your own ideas to life.
- Remote-first setup: work from Ukraine or anywhere in Europe.
- Unlimited paid time off, plus company-wide holidays.
- Software and AI tools you need for your work are covered.
- Budget for conferences, courses and professional development.
Hiring Process
recruiter interview → technical interview → hands-on coding → final interview with the co-founder → reference check and offer