Senior Computer Vision Engineer, Retail AI Systems

Scandit gives people superpowers. Whether enabling delivery drivers to make quicker deliveries, matching a patient with their medication, or allowing retailers to make store operations more efficient, our technology automates workflows. It provides actionable insights to help businesses in a variety of industries. Join us as we continue to expand, grow, innovate, and help take Scandit to the next level.

We are now building a new generation of technology for retail: a computer vision–driven system that helps retailers to increase their profit margins through better operational insight and automation. As a Senior Computer Vision Engineer, you will play a leading role in taking this product from 0 to 1, owning key technical decisions and delivering production-grade vision capabilities end to end.

You will own the technical direction for action recognition in real‑world retail environments: from defining how we collect and annotate video data, to prototyping and evaluating models, to iterating on precision, recall and end-to-end alert latency under production‑like conditions. You'll work closely with product, data, and engineering stakeholders to validate the riskiest assumptions quickly and cost‑effectively.

If you enjoy turning ambiguous, high‑impact problems into working ML products – and have experience building commercial computer vision systems for action recognition, autonomous checkout, worker safety, or similar applications – we'd love to talk.

About the role

As a Senior Computer Vision Engineer, you will be responsible for leading the technical discovery and early development of Scandit's new solution – from validating the riskiest assumptions to building and iterating on the first end-to-end prototypes. You will work closely with product, other engineering teams, and external stakeholders to turn real-world video data into robust, privacy-aware computer vision models that can operate in live retail environments.

This role connects cutting-edge CV/ML research with real-world product constraints – requiring both deep technical expertise and a pragmatic, experimental approach to building production-ready systems under ambiguity and time pressure.

What you will do

• Defining and prioritizing technical experiments to validate key risks (e.g. precision, recall, latency) for computer vision models in retail stores
• Designing and implementing end-to-end CV/ML pipelines on real-world video data, from data ingestion and preprocessing through model training, evaluation, and deployment
• Setting up and refining the human annotation workflow to create high-quality training and test datasets from video streams
• Collaborating with product managers and engineering leaders to clarify requirements, align on milestones, and translate business needs into technical roadmaps
• Selecting, adapting, and optimizing state-of-the-art computer vision architectures for suspicious behavior and action detection in unconstrained environments
• Providing technical leadership in the space of video-based computer vision applications, helping shape best practices and future hiring for the team

Who you are

We are looking for a senior computer vision / machine learning engineer who has successfully built and shipped real-world products, ideally involving action recognition on video. You combine deep hands-on technical expertise with a pragmatic, experimental mindset and are comfortable working in a high-ambiguity, 0→1 product environment. You should enjoy collaborating closely with product and engineering stakeholders, shaping the technical direction, and iterating quickly on ideas to validate the riskiest assumptions.

• University degree in Computer Science, Electrical Engineering, Mathematics or a related technical field (advanced degree is a plus but not mandatory)
• Significant hands-on experience in computer vision and machine learning, including designing, training, evaluating and deploying models in production
• Proven track record of building end-to-end CV/ML systems from 0→1 (ideally commercial products rather than purely academic projects)
• Strong expertise with video-based pipelines and human action or behavior recognition (e.g. retail,…