Senior ML Ops Engineer — Marketplace Platform

Apartment List; United States; On-site; USD 170,000 - 230,000; Full time

Benefits offered by this job

Equity

Job summary

Apartment List is hiring a Software Engineer for the Marketplace team to bridge full-stack product engineering and ML operations. You will build search/ranking features, support ML model deployment pipelines, and collaborate with data scientists to productionize models.

The role blends feature work with ML infrastructure, requiring comfort switching contexts and growing depth in both areas while coordinating with a distributed engineering team.

Qualifications

• 5+ years of professional software engineering or ML Ops experience.
• Proficiency in at least one backend language (Ruby/Javascript, Go, Python).
• Exposure to ML concepts and interest at the boundary of software engineering and ML.

Responsibilities

• Build and maintain full-stack features across marketplace products including search, ranking, and renter-facing UI.
• Support and extend ML Ops infrastructure—model deployment pipelines, feature stores, real-time data pipelines, and monitoring—on Chalk and Vertex AI.
• Collaborate with data scientists to bring models into production reliably and at scale.
• Write clean, well-tested code and participate in code reviews.
• Contribute to technical planning and break down complex problems into executable work.
• Address performance, reliability, and scalability issues in existing systems.
• Communicate progress and surface blockers early.

Skills

Backend/Full-stack

ML Ops

SQL

Cloud (GCP/AWS/Azure)

Cross-timezone collaboration

Ownership & communication

Tools

Vertex AI

MLflow

Kubeflow

Chalk feature store

Job description

Apartment List is hiring a Software Engineer for the Marketplace team to bridge full-stack product engineering and ML operations. You will build search/ranking features, support ML model deployment pipelines, and collaborate with data scientists to productionize models.

The role blends feature work with ML infrastructure, requiring comfort switching contexts and growing depth in both areas while coordinating with a distributed engineering team.