Senior Machine Learning Engineer, Digital Twin Platform

What you'll do

• Design and deploy machine learning models to track real-time inventory levels and shelf dynamics across thousands of retail locations.
• Manage the full ML lifecycle including problem framing, data exploration, model training, evaluation, and production deployment.
• Build infrastructure to ingest retail partner data and collect novel inventory observations for modeling pipelines.
• Develop systems to predict in-store stocking dynamics and provide accurate inventory estimates for search and logistics.
• Integrate machine learning outputs into live products at scale to improve the user experience.
• Define the technical direction of the modeling practice within a high-performance, fast-paced team environment.
• Collaborate with software engineers and computer vision experts to integrate advanced technologies into the Digital Twin Platform.

What we're looking for

• Minimum of 5 years of experience developing and deploying machine learning models in production environments.
• Proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Experience with large-scale data pipelines involving structured and unstructured data at scale.
• Experience with cloud infrastructure (AWS, GCP, or Azure) and familiarity with ML platform tooling for training, versioning, and serving.
• Bachelor's degree or higher in Computer Science, Machine Learning, Statistics, or a related technical field, or equivalent practical experience.
• Preferred experience in computer vision, inventory forecasting, demand sensing, or spatial/temporal modeling.
• Familiarity with real-time inference systems and low-latency, high-throughput environments.
• Experience collaborating with computer vision teams or incorporating vision-based signals into ML systems.