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

📋 Description

• Design, develop, and implement machine learning models for real-time insights into in-store inventory levels and shelf stocking behaviors.

• Take ownership of the complete ML lifecycle, encompassing problem definition, data exploration, model training, evaluation, and deployment into production.

• Collaborate effectively 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 the collection of inventory observations.

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

⛳️ Requirements

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

• Strong expertise in Python programming.

• Proficient in using frameworks such as TensorFlow, PyTorch, or scikit-learn.

• Experience with large-scale data pipelines.

• Familiarity with both structured and unstructured data at scale.

• Experience with cloud platforms such as 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 similar spatial/temporal modeling challenges.

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

• Preferred: experience in independently managing projects from initial concept to production.

• Preferred: background in retail, supply chain, or e-commerce sectors.

• Preferred: experience in collaboration with computer vision teams or integrating vision-based signals.