Wisy is building the intelligence layer for retail execution. We're an AI platform that guides field teams to take the right action, in real time, in every store, turning teams of field workers into a superpowered workforce. Backed by 8VC, Google and Nvidia.

Role

Machine Learning Engineer

Full-time, Remote

We are seeking a highly skilled, hands-on Machine Learning 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.

What you'll do

• 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.

What we're looking for

• 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.

What we value

• 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.

Nice to have

• 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.