Staff Machine Learning Engineer, Team Lead

Attentive is an AI marketing platform focused on 1:1 personalization, redefining brand and customer connections. The role involves leading the Machine Learning Engineering team to develop advanced ML models for personalized shopping experiences, collaborating with Product Management and Engineering teams.

Responsibilities:

• You have a proven track record of building systems that maintain a high bar of quality
• You deeply loathe regressions and take proactive steps to protect against them through a variety of testing techniques
• You are a collaborator, technical leader, and a great communicator
• You are constantly improving the quality of the project you are working on, both via direct contributions as well as long-term advocacy for larger-scale changes
• You are enthusiastic about the high impact, fast-paced work environment of an late-stage startup

Requirements:

• 10+ years experience is ideal
• You have worked professionally building systems for 6+ years with experience on a single system long enough to see the consequences of your decisions
• Experience with TensorFlow/Pytorch, xgboost, pandas, matplotlib, SQL, Spark or similar tools
• You have proficiency or experience with Python
• You have extensive experience using machine learning and data analysis, or similar, to build scalable systems and data-driven products, working with cross-functional teams
• You have a proven track record of building scalable, efficient, automated processes for large-scale data analyses, model development, model validation, and model implementation from modern research
• You have led cross-functional machine learning projects across teams
• You have a proven track record of building systems that maintain a high bar of quality
• You deeply loathe regressions and take proactive steps to protect against them through a variety of testing techniques
• You are a collaborator, technical leader, and a great communicator
• You are constantly improving the quality of the project you are working on, both via direct contributions as well as long-term advocacy for larger-scale changes
• You are enthusiastic about the high impact, fast-paced work environment of a late-stage startup