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.
Machine learning engineer in video understanding
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описание
задачи
- 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
требования
- 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, autonomous checkout or similar domains).
- Hands-on experience with vision transformers for temporal video understanding.
- Solid software engineering skills (e.g. Python and modern ML/CV frameworks) and experience working with real-world, noisy data
- Ability to work in a dynamic, high-uncertainty environment, prioritize experiments, and iterate quickly on technical approaches
- Ability to collaborate effectively with cross-functional teams (e.g. product, backend, data, operations) and communicate complex technical topics clearly in English (B2 level or higher)
- Eligible to work in the hiring location
- Будет плюсом: Experience fine-tuning Vision-Language Models (VLMs) is a strong plus; Experience with privacy-aware or GDPR-compliant data pipelines, especially for video data; Background in building or selecting annotation tools and workflows for computer vision training data; Prior work on retail, autonomous stores using computer vision
условия
- A highly skilled team and a fun environment where you can put your enthusiasm for cutting-edge technologies to use
- Hackathons
- Flexible, office, hybrid or home working
- People-first culture
- Global team outings
- Festive/end of year all company celebrations
- Your birthday off
- An attractive individual equity plan in a high growth company
- Excellent office infrastructure, optimized for hybrid working in Zurich, Warsaw, Tampere, and London.
- Excellent support for remote work across Switzerland, Finland, Poland, UK, Italy and Germany
- Specific benefits related to the location you are joining
навыки
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