Member of Technical Staff - Applied ML, RecSys

The role

You will own applied ML work end-to-end for recommendation system workloads. You will adapt Liquid Foundation Models for enterprise customers needing personalization and ranking capabilities.

What you will do

• Act as the technical owner for enterprise customer engagements involving recommendation and ranking workloads
• Translate customer requirements into concrete specifications for recommendation models
• Design and execute data pipelines for user interaction data, feature engineering, and training data curation at scale
• Fine-tune and adapt large-scale sequential recommendation models for customer-specific use cases
• Design task-specific evaluations for recommendation model performance and interpret results
• Build reusable applied tooling and workflows that accelerate future customer engagements

Required qualifications

• Hands-on experience building or fine-tuning recommendation models at scale
• Experience with sequential recommendation architectures, user behavior modeling, or large-scale ranking systems
• Strong intuition for data quality and evaluation design in recommendation contexts
• Experience with large-scale data pipelines for user interaction data and feature engineering
• Proficiency in Python and PyTorch with autonomous coding and debugging ability

Nice to have

• Experience with transformer-based recommendation architectures (HSTU, SASRec, BERT4Rec, or similar)
• Experience delivering recommendation systems to external customers with measurable business outcomes
• Familiarity with serving recommendation models under latency and throughput constraints

Benefits

• Competitive base salary with equity
• 100% of medical, dental, and vision premiums for employees and dependents
• 401(k) matching up to 4% of base pay
• Unlimited PTO
• Company-wide Refill Days throughout the year

About the company

Spun out of MIT CSAIL, liquid-ai builds general-purpose AI systems that run efficiently across deployment targets. They partner with enterprises across consumer electronics, automotive, life sciences, and financial services.