Machine Learning Engineer

Role Overview

As a Machine Learning Engineer on the Foundations team, you will own the full machine learning lifecycle—from POCs to production systems, including deployment, monitoring, and maintenance. You will build scalable ML solutions and improve model performance and scalability.

Responsibilities

• Create production-ready, scalable ML solutions
• Own the end-to-end ML lifecycle: POC creation, deployment, monitoring, and ongoing maintenance
• Optimize performance and scalability of machine learning models
• Design and run offline experiments to validate algorithm changes against key business metrics
• Engage in continuous learning and development to improve models and processes

Requirements

• 2+ years of experience applying machine learning in an industrial/production setting with a track record of impactful results
• Strong expertise in ML algorithms and frameworks
• Hands-on experience with training, tuning, and deploying models in production
• Strong software design and development skills in Python
• Experience in at least one applied area:
  • LLMs, Transformers, Recommendations, Personalization
• Excellent communication skills (written and verbal) and strong interpersonal skills

Preferred / Nice-to-have

• Deeper specialization across one or more applied domains (LLMs/Transformers/Recommendations/Personalization)

Work Arrangement (Remote/Hybrid)

• Hybrid model: candidates near a Shipt office/workspace in Birmingham, San Francisco, or Minneapolis may work from home with leader approval or work from the office.
• Some roles may require full-time in-office presence.

Compensation

• Pay Range: $76,100–$121,000 (guideline; total compensation may vary by qualifications, skill level, competencies, and work location).