Liquid AI

Member of Technical Staff - Applied ML, RecSys

Liquid AI
Apply
5 months ago
Boston, MA, USASenior
H1B Sponsor

Responsibilities

  • Own enterprise customer engagements involving recommendation and ranking workloads as the technical owner.
  • Translate customer requirements into concrete recommendation-model specifications.
  • Design and execute data pipelines, feature engineering, and training-data curation for user interaction data at scale.
  • Fine-tune and adapt large-scale sequential recommendation models for customer-specific use cases.
  • Design task-specific evaluations for ranking quality, latency, and throughput and interpret the results.
  • Build reusable applied tooling and workflows to accelerate future customer engagements.
  • Balance model quality, latency, and business impact while communicating technical decisions to customers.

Requirements

  • 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 understanding of data quality and evaluation design for recommendations, including offline metrics, A/B testing, and business-metric alignment.
  • Experience building large-scale data pipelines for user interaction data and feature engineering.
  • Proficiency in Python and PyTorch with autonomous coding and debugging ability.
  • Experience with transformer-based recommendation architectures such as HSTU, SASRec, or BERT4Rec is preferred.
  • Experience delivering recommendation systems to external customers with measurable business outcomes is preferred.
  • Familiarity with serving recommendation models under latency and throughput constraints is preferred.

Benefits

  • 100% employer-paid medical, dental, and vision premiums for employees and dependents
  • 401(k) matching up to 4% of base pay
  • Unlimited paid time off
  • Company-wide Refill Days throughout the year
  • Competitive base salary with equity
  • Enterprise customer engagements involving real production recommendation systems

Tech Stack

Categories

Data EngineeringML Engineering
Liquid AI

About Liquid AI

51-200 employees

We build efficient general-purpose AI at every scale.