Senior Machine Learning Engineer - Machine Learning Infrastructure

Position Overview

• Location Type: NYC or US Remote
• Employment Type: Full-Time
• Salary: Not provided

Flip.shop is a rapidly growing social commerce company that recently raised $144 million and has a valuation of $1.05 billion. They are redefining the shopping experience by giving consumers a voice. This role focuses on building and optimizing the infrastructure that powers their machine learning systems, enabling personalized shopping experiences and driving business growth.

Responsibilities

• Design and implement scalable infrastructure for deploying, monitoring, and maintaining machine learning models in production environments.
• Design and implement machine learning systems for feeds, ads, and search ranking models.
• Optimize the serving and training infrastructure of machine learning models.
• Enhance the workflow for model training and serving, data pipelines, storage systems, and resource management within multi-tenancy machine learning systems.
• Build tools to automate workflows for model training, testing, and deployment.
• Ensure the infrastructure supports high-performance model inference at scale, minimizing latency and maximizing throughput.
• Work closely with data scientists, machine learning engineers, and DevOps teams.
• Build robust monitoring systems to track model performance and infrastructure health.
• Implement best practices in infrastructure security, data privacy, and compliance.

Requirements

• Strong understanding of machine learning principles and techniques.
• Experience with designing and implementing scalable infrastructure for machine learning systems.
• Proficiency in programming languages such as Python.
• Experience with cloud platforms (e.g., AWS, GCP, Azure).
• Familiarity with DevOps practices and tools.
• Ability to collaborate effectively with cross-functional teams.

Company Information

• Company: Flip.shop
• Industry: Social Commerce
• Funding: Recently raised $144 million, valuation of $1.05 billion.
• Mission: Redefining the shopping experience by giving consumers a voice.
• Culture: Fast-paced, collaborative, innovative.