Orcrist is building a next generation data intelligence platform using cutting-edge technologies. We're handling petabyte-scale data with sub-second queries. Our product is a Kubernetes‑based platform delivered as B2B SaaS or as a self‑hosted on‑prem solution, including air‑gapped deployments. We enable customers across defense, law enforcement, and enterprise to turn mission-critical data into actionable intelligence.
Role
We are looking for a hands-on Machine Learning Engineer to develop and productionize modern computer vision and visual language capabilities across major intelligence and public safety projects. You will work directly with state-of-the-art and open-source computer vision models, visual language models (VLMs), and related AI technologies — training, evaluating, fine-tuning, and optimizing them for real-world use cases.
You will work on challenging problems including object recognition and identification, image and document understanding, geospatial data, satellite imagery, and large-scale visual data. The role combines model development with practical engineering: building data pipelines and scrapers, running experiments, and taking promising approaches into reliable systems.
This is a highly hands-on role for someone with exceptional learning ability, strong analytical and engineering skills, and a genuine interest in applying AI to complex problems in the intelligence and public safety domain. You will work closely with other engineers, technical leadership, and cross-functional teams to turn ideas and experiments into impactful capabilities.
What you’ll do
- Develop, train, evaluate, and fine-tune computer vision and visual language models.
- Work on object recognition, detection, classification, and identification.
- Build data pipelines, scrapers, and workflows for large-scale visual and geospatial datasets.
- Experiment with state-of-the-art and open-source models and turn promising approaches into reliable systems.
- Work with satellite imagery, geospatial data, sensors, and other visual intelligence sources.
- Take ownership of experimental projects and rapidly explore new ideas and technologies.
- Collaborate closely with other engineers and technical leadership on key initiatives.
- Travel every 2–4 weeks for architecture reviews and team events.
About you
- Bachelor's degree or higher in Computer Science, Physics, Mathematics, or a related field; with excellent grade record from a leading university (Master's preferred).
