Compensation Overview

Location: Carlsbad, California OR Fully Remote

About the Opportunity:

We are looking for a talented Machine Learning Engineer to join our team and deliver machine learning-driven products. The right candidate will work on development, deployment, and lifecycle management of machine learning models for various large-scale applications (natural language understanding, web search and ranking, recommendation, personalization, dialog/conversation management).

From your first day, you will make a valuable — and valued — contribution. We are a fast-growing company where no one is a bystander. We offer you the opportunity to delight millions of consumers around the world while gaining meaningful experience across a variety of disciplines.

Keywords:

Machine learning, natural language processing, learning-to-rank, online learning, deep learning, interactive machine learning, machine teaching, conversational agents, human computer interaction

Duties and Responsibilities:

• Design, implement, and deploy machine learning algorithms.
• Manage machine learning algorithm lifecycle.
• Coordinate data collection and annotation efforts.
• Work with real-time data and content coming from various data sources.
• Manage machine learning data pipelines. 
• Design tests for machine learning algorithm effectiveness and performance monitoring.
• Design tools and interfaces for interactive machine learning and teaching.
• Research and development on cutting-edge machine learning technologies.

Qualifications and Skills:

• Graduate degree in Computer Science with a strong background in machine learning required.
• Strong problem-solving abilities, solid background in algorithms and data structures required.
• Strong programming skills in Python and Scala required. Experience in other programming languages (eg. Java, R, Haskell) a plus.
• Solid knowledge of machine learning tools (eg. scikit-learn, tensorflow, keras, pytorch, Spark MLlib) required.
• Experience with distributed and streaming data technologies (eg. Hadoop, Spark, Kafka) required.
• Experience with building and deploying API’s with Docker and Kubernetes required.
• Experience with natural processing tasks (eg. named entity recognition, language modeling, vector representations) required.
• Experience with Elastic Search, Lucene a plus but not required.
• Experience with ranking algorithms a plus but not required.
• Experience with interactive machine learning (eg. active learning, reinforcement learning, machine teaching) a plus but not required.

The US base salary range for this role is between $160,000 and $220,000 annualized plus bonus, equity value (where applicable) and benefits. Your base pay will depend on your experience, location, skills and qualifications.