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Scandit is building a new generation of computer vision technology for retail, designed to help retailers increase profit margins through operational insight and automation. As a Senior Computer Vision/Machine Learning Engineer, you will own the technical direction for action recognition in real-world retail environments and play a leading role in taking this product from 0 to 1.
You will be responsible for leading technical discovery and early development, from validating the riskiest assumptions to building and iterating on end-to-end prototypes. 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.
Key responsibilities include:
- Defining and prioritizing technical experiments to validate key risks (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 human annotation workflows 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 video-based computer vision applications, helping shape best practices and future hiring for the team
You will work closely with product, data, and engineering stakeholders to validate assumptions quickly and cost-effectively, turning ambiguous, high-impact problems into working ML products.
REQUIREMENTS:
- University degree in Computer Science, Electrical Engineering, Mathematics, or 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; experience fine-tuning Vision-Language Models (VLMs) is a strong plus
- 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 (product, backend, data, operations) and communicate complex technical topics clearly in English (B2 level or higher)
- Eligible to work in the hiring location
NICE TO HAVE:
- 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 or autonomous stores using computer vision
