Location: Munich (Hybrid)
Type: Full-time

Company Overview

We are working with a fast-growing Vision / AI software company building production-grade computer vision systems for the food and retail sector. Their products help customers reduce food waste, improve operational efficiency, and contribute to sustainability goals by enabling better decision-making through real-time visual intelligence.

With an international footprint across Europe, the US, and Asia, they combine startup speed with real-world deployments at large enterprise customers.

The Role

We are looking for a Senior Machine Learning Engineer to take hands-on technical ownership of a key vision product that is moving into field testing with major retail partners in Germany.

This role is ideal for someone who enjoys being deeply involved across the entire ML lifecycle - from model development and training through to deployment on edge devices at customer sites. You will act as a hands-on technical lead for the product, driving model improvements, performance validation, and production rollouts.

Key Responsibilities Model Development
  • Design, implement, and iterate on deep learning architectures for real-time object tracking and event detection
  • Train and optimize object detection models using production datasets and domain-specific video data
  • Continuously improve model robustness for real-world conditions (lighting changes, occlusions, camera angles, motion blur, etc.)
Performance Evaluation & Validation
  • Build and execute evaluation workflows for accuracy latency benchmarking
  • Test models using benchmark video datasets and dedicated hardware setups
  • Monitor model performance regressions and validate incremental updates before release
Deployment & Integration (Edge / Production)
  • Own the technical process of deploying model updates into production systems
  • Ensure stable integration of models into the wider software stack running on-site
  • Support field testing cycles, troubleshooting and optimizing performance on edge devices
Tooling & Pipelines
  • Maintain and improve internal pipelines for:
    • automated model training
    • data versioning
    • performance testing
    • reproducible experimentation
  • Drive best practices across model development and deployment workflows
Requirements
  • 5–8 years experience in Machine Learning / Deep Learning / Computer Vision
  • Strong proficiency in Python PyTorch
  • Hands-on experience training object detection models (e.g., YOLO-style / Faster R-CNN / transformer-based detectors, etc.)
  • Solid software engineering skills in a Linux environment
  • Strong ownership mindset: able to maintain and advance the full ML stack end-to-end
  • Motivated to learn and apply new methods and improve production quality
Must Have
  • Native German speaker (customers and field partners are Germany-based)
Nice to Have
  • Experience deploying ML models to edge devices / embedded environments
  • Familiarity with performance profiling / inference optimization
  • Experience with real-time video pipelines and production CV systems
What’s On Offer
  • Hybrid working model in Munich
  • Flat hierarchies, high ownership, hands-on culture
  • International, multicultural environment with colleagues across multiple regions
  • Direct impact on a product entering real-world rollout with major German retailers
  • Benefits/perks including mobility options, company events, and additional corporate benefits