Sr Machine Learning Engineer, Applied Research Science (AI)

TL;DR

Sr Machine Learning Engineer, Applied Research Science (AI): Build cutting-edge technology using deep learning and machine learning to personalize hirify.global, partnering with teams to improve ML models for Homefeed, Ads, Growth, Shopping, and Search. Focus on leveraging data-driven methods and unique properties of data to improve candidates retrieval and contributing to a high-impact environment with quick experimentation and product launches.

Location: US based applicants only

Salary: $177,309—$310,291 USD

Company

hirify.global Machine Learning engineers build personalized experiences to help Pinners create a life they love.

What you will do

• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize hirify.global
• Partner closely with teams across hirify.global to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
• Work in a high-impact environment with quick experimentation and product launches
• Keeping up with industry trends in recommendation systems

Requirements

• 4+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
• MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences, related field, or equivalent experience.

Nice to have

• Publications at top ML conferences
• Expertise in scalable realtime systems that process stream data
• Passion for applied ML and the hirify.global product

Culture & Benefits

• Workplace should be equitable, inclusive, and inspiring for every employee.