Machine Learning Engineer (Computer Vision & VLM)

About this role

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).