Machine Learning Engineer, Catalog & Knowledge Graph (Staff/Senior)

The General ML team is dedicated to building a multi-faceted machine learning foundation at Instacart. 

We are utilizing machine learning to develop catalog solutions, including product taxonomy classification and catalog data anomaly detection. We are developing the Knowledge Graph and employing graph learning to shape the understanding of products for machine learning applications. In addition, we are creating content that inspires customers to discover new products on Instacart.

We are looking for machine learning engineers to advance this initiative, establish the foundation for a variety of machine learning applications at Instacart, and serve millions of households.

As a senior/staff machine learning engineer on the General ML team

• You use your strong engineering and machine learning skills to analyze problems and propose creative solutions in related team fields (catalog, knowledge graph, and inspirational content).

• You build the vision and roadmap for your field and prioritize the work that best aligns with business objectives.

• You work multi-functionally with other partners/teams to define goals, build alignments and drive projects. 
• You are responsible for the success of projects in your field and hold yourself accountable for the outcomes of each milestone.

• You are a thought leader in your field, mentor junior engineers, and help the team grow and evolve.

MINIMUM QUALIFICATIONS

• A graduate degree in artificial intelligence, machine learning, or equivalent self-study and experience.
• Extensive experience in natural language processing, knowledge graph, computer vision, text mining, and/or information extraction.
• Comfortable with learning and using state-of-the-art machine learning algorithms in the field.
• Strong programming skills and experience in Python, data manipulation (SQL, Spark, Pandas), and popular machine learning tools (PyTorch, Tensorflow, Scikit-learn, XGBoost), or equivalent experience.

• Familiar with works related to the product catalog, taxonomy enrichment, product enrichment, graph learning, and/or collaborative filtering.
• Strong communication skills and previous experience leading projects with multi-functional partners.
• Experience in handling projects of significant complexity and ambiguity.
• Strong engineering background and can develop end-to-end machine learning solutions.
• Experience contributing to research communities or efforts, including publishing papers in major conferences or journals.