This is a fully remote position, open to applicants in United States.

📋 Description

• Create, develop, and implement machine learning models for real-time analysis of in-store inventory levels and shelf stocking behaviors.

• Manage the complete ML lifecycle from problem definition and data analysis to model training, assessment, and deployment in production.

• Collaborate with software engineers, computer vision specialists, data scientists, and product managers.

• Contribute to the infrastructure of the Digital Twin Platform, which includes data ingestion from retail partners and innovative inventory observation systems.

• Assist in establishing the technical direction for the modeling practice.

• Foster product innovation and achieve significant business impact at scale.

⛳️ Requirements

• Over 5 years of experience in developing and deploying machine learning models in production settings.

• Excellent skills in Python.

• Familiarity with TensorFlow, PyTorch, or scikit-learn.

• Experience with large-scale data pipelines and managing structured as well as unstructured data at scale.

• Proficient in using AWS, GCP, or Azure.

• Knowledge of ML platform tools for model training, versioning, and serving.

• A Bachelor's degree or higher in Computer Science, Machine Learning, Statistics, or a related technical discipline, or equivalent practical experience.

• Preferred: experience in computer vision, inventory forecasting, demand sensing, or related spatial/temporal modeling.

• Preferred: familiarity with real-time inference systems and low-latency, high-throughput ML serving.

• Preferred: experience leading projects independently from conception to production.

• Preferred: exposure to retail, supply chain, or e-commerce industries.

• Preferred: experience working with computer vision teams or integrating vision-based signals into ML systems.