Study and transform data science prototypes into production-ready machine learning models.
Train, retrain, and monitor machine learning systems and models to ensure optimal performance.
Collaborate with cross-functional teams to integrate machine learning solutions into production systems and applications.
Identify and address potential issues in data distribution that may impact model performance in real-world scenarios.
Ensure algorithms generate accurate and relevant recommendations.
Build and maintain high-performance, scalable machine learning data pipelines to support best-in-class restaurant technology solutions.
Design and develop data pipelines (batch and streaming) to ingest data from various sources, including point-of-sale systems, back-of-house operations, and other platforms.
Leverage a mix of open-source frameworks (PySpark, Kubernetes, Airflow, etc.) and cloud-based tools (Informatica Cloud, Snowflake, Domo, etc.) to build and maintain the data platform.
Implement and manage production support processes, including data lifecycle management, data quality assurance, and data integration.
Develop scalable REST APIs in Python to expose machine learning models and data services.
Qualifications
Bachelors degree in Computer Science, Engineering, Business Administration, Economics, Finance, Statistics or a related field.
Minimum of 4 years of experience.
Experience in Customer intelligence, pricing models, or mixed media modeling.
Julia language experience is a plus.
Excellent time management and organizational skills.
Strong analytical and problem-solving skills.
Strong communication skills.
Excellent time management and organizational skills.
In-depth knowledge of machine learning frameworks like Keras, and TensorFlow.
AWS platform development experience (EKS, S3, API Gateway, Lambda, etc.).
Deep understanding of probability, statistics, and algorithms.