Senior Machine Learning Engineer, Digital Twin Platform

What you'll do

• Design and deploy machine learning models to track real-time inventory levels and stocking dynamics across thousands of retail locations.
• Manage the full ML lifecycle including problem framing, data exploration, model training, evaluation, and production deployment.
• Build infrastructure for ingesting retail partner data and collecting novel inventory observations for modeling pipelines.
• Develop systems to provide high-accuracy inventory estimates for search and logistics products at scale.
• Define the technical direction of the modeling practice within a fast-paced, startup-style team environment.
• Integrate complex machine learning outputs into live production systems to improve the user experience.
• Collaborate with computer vision engineers and data scientists to incorporate vision-based signals into broader ML systems.

What we're looking for

• Bachelor's degree or higher in Computer Science, Machine Learning, Statistics, or a related technical field (or equivalent experience).
• 5+ years of experience developing and deploying machine learning models in production environments.
• Strong proficiency in Python and experience with ML frameworks like 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 ML platform tooling for training, versioning, and serving.
• 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.