Senior ML Engineer — Recommender Systems & LLM Architect

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

Benefits offered by this job

Equity

401(k) plan

Medical benefits

Job summary

Wonder in New York seeks a hands-on technical leader to own model architecture across ranking, retrieval, and recommendation. This is not management; you will guide technical direction and mentor engineers.

You will collaborate with product and platform teams, drive end-to-end evaluation, and bring state-of-the-art IR and LLM techniques into production, balancing performance and scalability. The role supports a hybrid work model with NY base salary in the range shown.

Qualifications

• MS/PhD in a quantitative discipline or equivalent experience.
• 6+ years building and shipping ML systems, including 3+ years operating at senior-level scope across teams/systems.
• Deep experience in recommendation systems, ranking, or information retrieval at scale.
• Proven track record with production deep learning in TensorFlow or PyTorch (training, serving, tuning on GPUs).
• Experience with Large Language Models and transformer architectures (fine-tuning, embeddings, latency-sensitive).
• Strong data engineering fundamentals: PySpark, Hive/SQL, Python data stack.
• Fluency with experimentation: designing A/B tests and guardrails.
• Experience with cloud ML infrastructure (AWS/SageMaker or equivalent).

Responsibilities

• Own the architecture of ranking and recommendation stack end to end (candidate retrieval, ranking, calibration, ensemble).
• Lead evolution of optimization objective toward long-term value with offline and online evaluation.
• Bring state-of-the-art IR and recommender techniques into production (LLMs, embeddings, sequential representations).
• Raise engineering and operational standards (scorecards, reproducible pipelines, observability).
• Partner with Product, Search Engineering, Ads, and Data Platform on roadmaps and data readiness.
• Mentor senior engineers and participate in hiring to grow technical depth.
• Translate technical trade-offs into business terms for product and executives.

Skills

ML Systems

Reco Systems

Info Retrieval

TensorFlow/PyTorch

LLMs

Python Stack

A/B Testing

Cloud ML

Mentoring

Executive Comms

Education

MS/PhD in quantitative field

Job description

Wonder in New York seeks a hands-on technical leader to own model architecture across ranking, retrieval, and recommendation. This is not management; you will guide technical direction and mentor engineers.

You will collaborate with product and platform teams, drive end-to-end evaluation, and bring state-of-the-art IR and LLM techniques into production, balancing performance and scalability. The role supports a hybrid work model with NY base salary in the range shown.