Principal Machine Learning Engineer

iHerb is on a mission to make health and wellness accessible to all. The Principal Machine Learning Engineer will tackle challenging problems and create scalable machine learning systems to enhance customer experience and automate core business processes.

Responsibilities:

• Partner with the Data Platform team in a two-way exchange of best practices
• Adopt common patterns and build effective abstractions across different machine learning pipelines that simplify existing machine learning processes and accelerate the modelling process from the business problem’s inception to deploying a model solution into production
• Develop horizontal solutions to robustly scale the team’s machine learning models and processes
• Build software with Object-oriented Design Patterns and Analysis (OOA and OOD) with an eye toward reducing technical debt and maintaining services at high availability
• Participate in requirements reviews, design reviews, and code reviews
• Research and prototype new technologies to support the rapid growth of the business
• Interact cross-functionally with a wide variety of technical teams and work closely with data and applied scientists to identify opportunities to improve on iHerb’s platform

Requirements:

• Strong coding experience (e.g. Java, C#, Python)
• Experience with gathering data from multiple sources using big data technologies (Spark, Hadoop, BigQuery, Athena, etc.)
• Experience building machine learning infrastructure following robust software engineering practices
• Knowledge of modern software development tools, systems, and practices (design patterns, CI/CD, git, unit testing, smoke testing, integration testing, job schedulers, cloud technologies like AWS Lambdas and Google functions, etc.)
• Exposure to all aspects of the software development life-cycle
• Experience with messaging technologies (Kafka, Google Pub/Sub, Kinesis, RabbitMQ, etc.)
• Experience with Docker and Kubernetes
• High degree of accuracy and attention to detail
• Excellent organization skills and ability to multitask
• Experience with Microsoft Office Suite (Word, Excel, PowerPoint)
• Generally requires a minimum of two (2) years relevant experience in applied machine learning or machine learning systems/infrastructure, and one (1) year of relevant work experience in machine learning engineering or related fields. (e.g., as a Machine Learning Engineer, ML Ops engineer, or related position)
• Bachelor's Degree in Computer Science, Electrical Engineering, or related field required
• Experience with Google Business Suite (Gmail, Drive, Docs, Sheets, Forms)
• Masters Degree preferred