We’re hiring a Senior Machine Learning Platform Engineer to build and scale the systems that enable production-grade machine learning and AI across Zip. This role sits at the intersection of data engineering and machine learning, focused on making ML systems reliable, observable, and scalable.
You will own the ML lifecycle end-to-end, from feature pipelines and model registry standards to CI/CD and model serving on Databricks (Azure). You’ll partner closely with Data Science, Analytics, and Engineering teams to ensure that models move efficiently from experimentation to production and deliver real business impact.
This is a high-impact role for engineers who enjoy building platforms, solving complex distributed systems problems, and enabling the next generation of AI-driven capabilities across the business.
Interesting problems you’ll get to solve
Own the ML Lifecycle (MLOps)
- Build and maintain batch and streaming feature pipelines
- Design and manage offline and online feature store patterns
- Define MLflow model registry standards and promotion workflows
- Deploy and operate scalable model serving endpoints
- Implement CI/CD for ML pipelines and model deployment
Build high-performance Spark systems
- Develop pipelines using PySpark and Spark SQL
- Optimize joins, partitioning, and shuffle-heavy workloads
- Improve reliability and cost-efficiency of distributed data jobs
- Support streaming workloads using Delta Live Tables
Operate and evolve the ML platform
- Manage Databricks clusters, jobs, and access controls
- Improve observability, alerting, and operational standards
- Contribute to Lakehouse architecture (Databricks and Snowflake)
- Implement governance, RBAC, and data quality standards
Enable AI innovation across the business
- Build infrastructure that accelerates experimentation and model deployment
- Support emerging AI use cases, including real-time and large-scale ML systems
What you’ll bring to the team
Experience
- 8+ years of experience in Machine Learning with a strong focus on production-grade ML and distributed data systems
- Demonstrated experience owning and operating ML systems end-to-end in production environments
Strong Spark Capability (Core Requirement)
- Advanced experience with PySpark and Spark SQL
- Strong understanding of Spark execution (joins, shuffles, partitioning)
- Experience building and optimizing reliable, scalable data pipelines
- Strong data engineering fundamentals including medallion architecture design, incremental/idempotent ETL patterns, and Delta Lake optimization (partitioning)
MLOps & ML Systems
- Experience operating ML systems in production
- Hands-on experience with MLflow (tracking + model registry)
- Experience managing feature stores (offline + online)
- Experience deploying and monitoring model serving endpoints
- Experience implementing CI/CD for ML workflows
Cloud & Platform Experience
- Experience working in Azure
- Production experience with Databricks and Delta Lake
- Experience integrating with CosmosDB or similar NoSQL key-value stores
- Experience designing orchestrated, production-grade data workflows (Databricks Workflows, Airflow, or ADF) with dependency management, backfills, and failure recovery
Nice to Have
- Delta Live Tables and streaming pipelines
- Iceberg or Lakehouse Federation experience
- Vector databases or LLM infrastructure
- Infrastructure-as-code experience
What you’ll get in return
Zip is a place where you’ll get out what you put in. The newness of our sector means we need to move at pace and embrace change, and our promise to you when you join the team is that you’ll feel empowered and trusted to make big things happen quickly.
We want you to feel welcome and as though you have the support to be yourself, and care for yourself at work. Because it’s important to us that you make the most of the opportunities you’ll get to grow your skills and your career, and be surrounded by smart, friendly people and leaders that have your back.
We think these are just some of the best things about being a Zipster. We will also offer you:
- Generous paid parental leave
- Leading family support policies
- Company-sponsored 401k match
- Learning and wellness subscription stipend
- Beautiful Union Square office with a casual dress code
- Industry-leading, employer-sponsored insurance for you and your dependents, with several 100% Zip-covered choices available