Machine Learning Engineer (Computer Vision & VLM) at Orcrist Technologies

Job description

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). Strong academic record and excellent analytical and problem-solving skills. Strong programming skills and experience developing or fine-tuning AI/ML models. Experience with computer vision, VLMs, image understanding, or related ML applications. Strong interest in data, analytics, and data pipelines. Exceptional ability and motivation to learn new technologies and domains quickly. Self-directed, hands-on, and comfortable working without close day-to-day management. Strong team player with clear and honest communication. Excellent German language skills. Eligible to work full-time in Germany and willing to undergo the required security clearance and background checks. Nice-to-haves Experience with georeferencing, satellite imagery, remote sensing, OpenStreetMap, or photogrammetry. Experience with large-scale data pipelines, cloud infrastructure, or ML deployment. Experience with sensors such as drones, antennas, or cameras. Background in computer vision research, e.g. Fraunhofer IGD or similar. Knowledge of Russian or Ukrainian language. Interest or experience in military, intelligence, defense, or public safety domains. What we offer Remote-first, Germany-wide: Work from wherever you do your best work, with regular team gatherings in Berlin and other off-site locations. Flexibility by default: Flexible working hours help you make work fit your life. Your setup, your way: Get a personal home-office equipment budget to create a workspace that works for you. 30 days of vacation: Take the time you need to recharge and come back with fresh energy. Keep growing: We invest in your personal and professional development. Get rewarded for impact: Performance bonuses are tied to agreed objectives and key results. A warm welcome: Every new team member gets a welcome goodie bag. Good people, good times: From summer and Christmas parties to regular team gatherings, we make time to celebrate together. A mission that matters: Work on challenges with tangible impact on public safety and national security.

Requirements

Must-haves

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.
Strong academic record and excellent analytical and problem-solving skills.
Strong programming skills and experience developing or fine-tuning AI/ML models.
Experience with computer vision, VLMs, image understanding, or related ML applications.
Strong interest in data, analytics, and data pipelines.
Exceptional ability and motivation to learn new technologies and domains quickly.
Self-directed, hands-on, and comfortable working without close day-to-day management.
Strong team player with clear and honest communication.
Excellent German language skills.

Nice-to-haves

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).
Experience with georeferencing, satellite imagery, remote sensing, OpenStreetMap, or photogrammetry.
Experience with large-scale data pipelines, cloud infrastructure, or ML deployment.
Experience with sensors such as drones, antennas, or cameras.
Background in computer vision research, e.g. Fraunhofer IGD or similar.
Knowledge of Russian or Ukrainian language.
Interest or experience in military, intelligence, defense, or public safety domains.

Application prep

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Keywords to mirror

kubernetesmachine learningaiml

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Vision

Professional Development