Senior Machine Learning Engineer

As a Senior Machine Learning Engineer on Shipt’s Foundations team, you will implement advanced machine learning models and help design and analyze experiments that address priority problems across pricing domains. You will operate as a subject matter expert in both machine learning and experimentation, validating how algorithmic changes affect important business metrics.

Key Responsibilities

• Implement cutting edge machine learning models to support foundational capabilities.
• Design and analyze advanced experiments in collaboration with product, business, and engineering teams to solve key challenges across multiple pricing domains.
• Serve as the subject matter expert in a machine learning domain or experimentation.
• Build advanced ML solutions and validate the impact of algorithmic changes on key business metrics.
• Present recommendations to key stakeholders based on analysis and experimental outcomes.

Required Qualifications

• 4+ years of experience applying machine learning and statistics in an industry setting, with a record of delivering impactful results.
• PhD or Masters in Computer Science, Statistics, or a related field.
• Experience building and deploying machine learning models.
• Experience with experiment design, rollout, analysis, and reporting.
• 4+ years of Python development.
• Experience presenting to stakeholders.
• Experience leading key technical projects and substantially influencing the scope and output of others.
• Bachelor's Degree or equivalent experience.

Technology Stack

• Python
• Artificial Intelligence (AI)
• Machine Learning (ML)

Education

PhD or Masters in Computer Science, Statistics, or a related field.

Benefits

• Medical, dental, vision and more
• 401k plan eligibility
• Discretionary vacation for exempt team members
• Paid holidays throughout the calendar year
• Paid sick leave
• Eligibility for an annual bonus
• Potential for restricted stock units based on role

Work Arrangement

• Remote roles: Remote (remote).
• Hybrid roles in Birmingham, AL: typically work in-office at least 2 days per week, with core in-office days on Wednesdays and Thursdays.
• Hybrid roles in Minneapolis, MN: typically work in-office at least 1 day per week on either Tuesday, Wednesday, or Thursday.
• Hybrid roles in San Francisco, CA: typically work in-office at least 1 day per week between Monday and Thursday.
• Certain roles may require in-office presence on a full-time basis.