Wisy está construyendo la capa de inteligencia para la ejecución en el punto de venta. Desarrollamos una plataforma de IA que guía a equipos globales para tomar acciones precisas en tiempo real — transformando el trabajo físico en una operación aumentada. Contamos con el respaldo de 8VC, Google y Nvidia.
Full Stack Engineer
Full-time, Remote, US/LATAM
We are seeking a highly skilled, hands-on Full Stack Engineer who thrives as a generalist to help us scale our production AI capabilities in complex, real-world retail environments. Rather than a theoretical research position, this is a highly applied engineering role where you will focus on building, debugging, and shipping production-ready models and robust data pipelines. We value breadth over depth in any single domain — specialized areas like computer vision are easy enough to pick up on the job. Working closely with a high-caliber team of engineers and data scientists, your practical execution will directly influence Wisy’s core platform, data flows, and future trajectory.
Lo que harás
- Train, debug, and ship any kind of model to solve practical retail data challenges — model type matters less than your ability to get it into production.
- Build, maintain, and optimize robust data engineering foundations, including scalable ETL/ELT pipelines.
- Take end-to-end ownership of data quality, data cleaning, and preprocessing workflows to ensure pristine model inputs.
- Build efficient pipelines for model inference and postprocessing, collaborating closely with backend and infrastructure engineers.
- Implement best practices in MLOps, including version control, model monitoring, reproducibility, and automated deployment pipelines.
- Own model evaluation using performance metrics to ensure stability and accuracy in production environments.
- Support internal tooling and improve the developer experience as it relates to model deployment and data visualization.
- Diagnose, troubleshoot, and optimize performance issues within existing production models and data pipelines.
- Create and maintain technical documentation and support onboarding of new team members.
- Contribute to sprint planning, estimations, and architecture discussions.
Lo que buscamos
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
- 3+ years of hands-on software or data engineering experience with an emphasis on production machine learning.
- Strong proficiency in training models with PyTorch or TensorFlow.
- Excellent programming skills in Python and strong database capabilities in SQL.
- Proven experience building operational data pipelines (ETL/ELT) and managing data quality frameworks.
- Solid understanding of MLOps concepts, containerization (Docker, Kubernetes), and cloud environments (AWS, GCP).
- Fluent in async collaboration and Agile development practices.
Lo que valoramos
- Clarity & Simplicity – Writing clean, maintainable, and scalable code is a must.
- Bias for Action – You take initiative and move quickly, even with ambiguity.
- Collaboration Over Ego – You work well with others, seek feedback, and respect every perspective.
- Curiosity & Growth Mindset – You stay on top of industry trends and continuously improve your skills.
- Customer Obsession – You build with the end user in mind and align work to real outcomes.
- Trust & Transparency – You communicate openly and own your responsibilities.
Sería un plus
- Experience with Computer Vision architectures, object detection models, or YOLO frameworks.
- Experience deploying models to resource-constrained edge or mobile environments.
- Familiarity with image annotation tools (e.g., CVAT, Label Studio) and labeling workflows.
- Experience working specifically within the retail, logistics, or consumer goods industries.