Senior Machine Learning Engineer, Real-Time Bidding - Remote

Overview

Trellis is a profitable, fast-growing Series A startup backed by top investors like General Catalyst, QED, NYCA, and Amex Ventures. Our mission: make shopping for home and auto insurance faster, smarter, and easier for everyday Americans. Powered by ML and GenAI, we help people find better insurance — saving them time, money, and stress. We’re fully remote, built for speed, and led by a third-time fintech founder with a track record of building public companies.

In Short

• Trellis is hiring a Senior Machine Learning Engineer to advance real-time bidding systems.
• Design, implement, and scale ML models for high-volume bidding decisions.
• End-to-end ownership of the ML lifecycle: data exploration, feature engineering, model training, deployment, and monitoring.
• Leverage Google Cloud Platform services and Python-based ML frameworks.
• Research, design, and implement advanced ML models for conversion rate prediction, value estimation, and pacing.
• Build robust feature pipelines with BigQuery and Dataflow.
• Deploy, monitor, and improve models in production using Vertex AI.
• Develop MLOps frameworks for automation.
• Collaborate with backend engineers to integrate models into bidding services.
• Contribute to experimentation frameworks and AB testing.

Requirements

• 5+ years of ML engineering experience.
• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience with cloud ML platforms, preferably GCP.
• Familiarity with MLOps practices.
• Strong data skills: SQL, feature engineering, big data processing.
• A pragmatic mindset for delivering improvements.

Benefits

• Flat, collaborative culture with growth opportunities.
• 75th-percentile competitive compensation.
• 100% remote work environment.
• Quarterly team bonding events.
• Unlimited vacation time.
• 100% employer-paid health insurance for employees.
• Flexible Spending Accounts (FSAs).
• 401(k) retirement savings plan.
• Bonuses and equity opportunities.
• Budget for home office equipment.