Staff Machine Learning Engineer

The role

You will own the layer between data science and infrastructure. You will run a managed feature store and build training and deployment platforms to enable data scientists to work independently.

What you will do

• Run the managed feature store by building patterns and tooling for defining, backfilling, and serving features.
• Make the feature store the starting point for model training.
• Build and improve automated training and deployment platforms.
• Turn repetitive data science steps into self-service agents and skills.
• Standardize training and retraining to be schedulable and reproducible.
• Scale batch scoring and low-latency online inference with autoscaling and cost controls.
• Extend monitoring for data drift, feature drift, prediction quality and serving health.
• Define standards for model and feature versioning, lineage, testing and documentation.

Required qualifications

• Deep hands-on experience as a platform or software engineer working in ML.
• Track record of platforms that served many models in production across multiple teams.
• Experience with feature stores and model deployment platforms, such as Databricks Feature Store, Feast, Tecton or equivalent.
• Strong CI/CD for ML (GitHub Actions, Jenkins, Azure Pipelines or similar).
• Experience with model registries and infrastructure as code with Terraform.
• Cloud expertise in AWS or Azure for ML deployment.
• Experience with Kubernetes and workflow orchestration.
• Strong command of batch and real-time serving, autoscaling, and latency and cost trade-offs.
• Ability to remove engineers from the deployment loop with self-service tooling.
• Ability to work well with ambiguity by gathering requirements and driving projects to completion.
• Depth in model development and common algorithms to be a technical partner to data scientists.

Nice to have

• Familiarity with PySpark, Databricks and monitoring tools such as Evidently AI

Benefits

• WFH office reimbursement
• Competitive compensation packages
• Generous equity
• Flexible health plans at every premium level
• Substantial subsidies that stand up to global standards
• Direct exposure to leadership team
• Paid global onsites twice yearly

Before you apply

• Initial Recruiter Call
• Hiring Manager Interview
• Skills Panel
• Leadership Conversation

About the company

Tilt uses mobile-first products and machine learning-powered credit models to recognize potential beyond credit scores. They are creating a new credit system for millions of customers worldwide.