PhD University Grad Machine Learning Engineer (USA)

At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love. We're looking for a PhD University Grad Machine Learning Engineer to join our engineering teams and work on cutting-edge research in machine learning and artificial intelligence.

As a Machine Learning Engineer at Pinterest, you'll work on tackling new challenges in machine learning and artificial intelligence. You'll contribute to large-scale recommendation systems, work on state-of-the-art applied machine learning projects, and build intelligent data-driven models.

Responsibilities:

• Contribute to cutting-edge research in machine learning and artificial intelligence
• Collect, analyze, and synthesize findings from data and build intelligent data-driven models
• Write clean, efficient, and sustainable code
• Use machine learning, natural language processing, and graph analysis to solve modeling and ranking problems
• Design, build, and test models to predict engagement for notifications
• Build content recommendation systems to power push, email, and in-app notifications
• Work on state-of-the-art large-scale applied machine learning projects
• Scope and independently solve moderately complex problems

Requirements:

• PhD in Computer Science, ML, NLP, Statistics, Information Sciences or related field required
• Machine Learning experience (ranking, computer vision, NLP, content recommendations, embedding, information retrieval etc)
• Experience with big data technologies (e.g., Hadoop/Spark) and scalable realtime systems
• Mastery of at least one systems language (Java, C++, Python) or one ML framework (Tensorflow, Pytorch, MLFlow)
• Proficiency with AI-native engineering
• Strong critical thinking and problem-solving skills
• Experience in research and in solving analytical problems
• Strong communicator and team player

Benefits:

• Base salary range: $174,078-$229,044 USD
• Equity eligibility
• Flexible work arrangements
• Opportunity to work on large-scale machine learning projects