Staff ML Engineer: Recommender Systems & LLM Architect

Blue Apron; New York (NY); Hybrid; USD 209,000 - 217,000; Full time

Benefits offered by this job

Equity in company

401(k)

Medical, dental, vision plans

Job summary

Wonder seeks a Staff Machine Learning Engineer in New York to own the end-to-end ranking and recommendation stack, including candidate retrieval, multi-objective ranking, and calibration. You will drive cross-team architectural decisions, mentor engineers, and push for rigorous evaluation and observability across models.

The role emphasizes production-ready ML systems, transformer models, and online experimentation, with a hybrid work model requiring in-office presence 3 days per week in NYC.

Qualifications

• MS/PhD in a quantitative field or equivalent experience.
• 6+ years building and shipping ML systems.
• 3+ years operating at senior-level scope across teams or systems.
• Production deep learning in TensorFlow or PyTorch.
• Experience with LLMs and transformer architectures.

Responsibilities

• Own the architecture of ranking and recommendation stack end to end.
• Lead the evolution of optimization objectives and offline/online evaluation.
• Mentor engineers, participate in design reviews and hiring.
• Collaborate with Product, Search Eng, Ads, and Data Platform to shape roadmaps.

Skills

ML systems

Recommendation systems

Information retrieval

Deep learning

TensorFlow

PyTorch

LLMs

Transformers

Python data stack

Experimentation

Cloud ML

PySpark

Hive/SQL

AWS/SageMaker

Leadership

Communication

Education

MS/PhD in a quantitative discipline

Tools

PySpark

Hive/SQL

Python data stack

AWS/SageMaker

Model deployment

Job description

Wonder seeks a Staff Machine Learning Engineer in New York to own the end-to-end ranking and recommendation stack, including candidate retrieval, multi-objective ranking, and calibration. You will drive cross-team architectural decisions, mentor engineers, and push for rigorous evaluation and observability across models.

The role emphasizes production-ready ML systems, transformer models, and online experimentation, with a hybrid work model requiring in-office presence 3 days per week in NYC.