Modern supply chains depend on seamless coordination across vast networks of facilities, equipment, and logistics operations. Yet critical visibility gaps remain places where decisions are made without complete information, where optimization is constrained by the limits of manual oversight, and where inefficiency compounds across thousands of sites.
We're building a computer vision and AI platform that changes this. By creating a unified intelligence layer across fragmented operations, we're enabling real-time understanding and automation where it matters most.
We're early, backed by Merantix Capital, and working with strategically important design partners in logistics and manufacturing. This is the kind of infrastructure problem that, once solved properly, scales across an entire industry.
As Senior Computer Vision Engineer, you'll be instrumental in taking our automation platform from early prototypes into production systems deployed across logistics networks. You'll report directly to our CTO/Co-founder and work alongside a growing engineering team.
This is a hands-on, high-ownership role for someone who wants to solve real-world problems at scale. You'll work on cutting-edge computer vision challenges real-time object tracking, multi-view 3D reconstruction, ID association, and behavioral anomaly detection in messy, industrial environments.
Key Responsibilities
CORE CV SYSTEM
Multi-camera fusion - Calibrate and fuse overlapping feeds into a single spatial model of the environment in real time.
Tag-free re-identification - Associate the same asset across cameras using appearance and motion alone. No RFID, no beacons.
3D scene understanding - Map 2D detections to real-world coordinates and maintain queryable spatial state over time.
Behavioral anomaly detection - Learned models that generalize across new sites, not brittle rule-based heuristics.
ML TRAINING & INFRASTRUCTURE
Training stack - Own the pipeline from raw site footage to deployed model: labeling, experiment tracking, model versioning, and automated validation before anything ships to a customer site.
Data flywheel - Design pipelines that turn live customer footage into training data at scale so model quality compounds with each new deployment.
EDGE & PRODUCTION
Edge deployment - Optimize for on-premise inference on commodity hardware.
Production quality bar - Define, monitor, and own what "good enough" means for mission-critical CV.
CUSTOMER & PRODUCT
Pilot site presence - Diagnose failures in the field. Operational realities feed directly into engineering decisions.
Technical leadership - Set standards for model development, code quality, and CV best practices as the team grows.
You are a highly skilled computer vision engineer with proven experience taking CV projects from research/prototyping into production. You're excited about solving hard technical problems in real-world industrial settings. You communicate clearly, work autonomously, and thrive in a fast-moving startup environment.
5+ years of hands-on experience in computer vision, AI/ML or robotics projects
Strong expertise in Python and/or C++ and modern ML frameworks (PyTorch, TensorFlow)
Deep understanding of computer vision algorithms, e.g. ByteTrack, DeepSORT etc
In-depth knowledge of CV tools and libraries: OpenCV, torchvision, YOLO, object detection/tracking frameworks
Production experience: you've taken at least one CV project from concept through deployment to end users
Advanced degree: MSc or PhD in Computer Science, Machine Learning, Robotics or adjacent
Cloud experience: hands-on work with at least one major provider (AWS, GCP, Azure)
Code quality: experience with code reviews, testing, and maintaining large codebases
Fluent English (German not required)
Experience with multi-camera systems, 3D tracking, or geospatial reasoning
On-premise or edge deployment experience (inference at the edge, privacy constraints)
Background in logistics, robotics, autonomy, or industrial automation
Experience with real-time systems or performance optimization for latency-critical applications
Hands-on data labeling & curation experience (understanding ground truth quality)
Entrepreneurial mindset: you're comfortable with ambiguity, move fast, and bias toward action
Prior experience in a startup or early-stage company environment
Experience with 3D reconstruction, SLAM, or structure-from-motion
Familiarity with sensor fusion (combining camera, LiDAR, radar)
Knowledge of
GDPR and privacy-preserving machine learning
Competitive salary + stock options (meaningful equity as an early engineer)
Brand new office on Berlin's AI Campus (Merantix HQ) where you can collaborate with hundreds of AI engineers across the ecosystem
Hardware & equipment allowance to ensure you have everything needed to thrive
Build the core team with us
We are an equal-opportunity employer and value diversity. We consider all applications equally regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply.
