Working Student — Computer Vision & Fullstack Engineer

Working Student, Computer Vision & Fullstack Engineer

Location: Remote

Hours: ~20h/week (working student status)

Start: ASAP

About the role

We build AI solutions for engineering, applying modern computer vision and ML to real engineering problems. You'll work across the full slice: training models, building the backend services that serve them, and shipping the interfaces engineers actually use.

What you'll work on

• Training and fine-tuning detection, OCR, and segmentation models on real and synthetic data
• Designing synthetic data and augmentation pipelines that transfer to production
• Classical CV preprocessing as fast, reliable baselines. Not everything needs a GPU
• Backend inference services and data pipelines in Python
• Packaging, deploying, and operating what you build

Must-have:

• Strong CS background, BSc completed from a reputable university. MSc in progress is welcome
• High ownership. You take problems end-to-end, ship without hand-holding, and own what you build in production

Computer Vision:

• Solid grasp of modern deep-learning vision: detectors, training loops, losses, evaluation, augmentation, overfitting and regularization
• Comfortable with PyTorch
• Working knowledge of classical / legacy CV with OpenCV. You should reach for these before throwing a GPU at every problem

Fullstack & DevOps:

• Hands-on fullstack experience, frontend and backend, in real projects
• Have built and deployed something end-to-end, not just localhost
• Docker, Linux shell, SSH, bash scripting
• CI/CD experience (GitHub Actions or similar)

Nice-to-have:

• Cloud-native: Azure, AWS or GCP, managed databases, object storage, IaC
• 3D vision / geometric deep learning: B-rep, STEP/IGES, OpenCASCADE, GNNs on CAD topology, point clouds, mesh processing
• Foundation models for vision (SAM, GroundingDINO, VLM finetuning)
• Interest in AI for engineering: CAD, manufacturing, technical documentation

What we offer:

• Strong compensation, above-market rates for working students
• Top-tier AI tools and budget covered
• Fast-paced environment. Small team, short feedback loops, your code ships the same week
• Flexibility. Remote-friendly, hours that work around your studies