Senior ML Engineer: Recommender Systems & Retrieval

GrubHub Inc.; New York (NY); On-site; USD 176,000 - 260,000; Full time

Benefits offered by this job

Equity

401(k)

Health insurance

Dental/ Vision

PTO

Parental leave

Job summary

Wonder, based in New York, seeks a senior to senior staff ML engineer to own the full architecture of ranking and recommendation systems. You will guide model retrieval, multi-objective ranking, and calibration while collaborating with product and platform teams to ensure scalable, measurable impact.

You will drive state-of-the-art information retrieval and learning to rank techniques, mentor engineers, and communicate trade-offs to executives.

Qualifications

• MS/PhD in a quantitative discipline (CS, Math, Physics, Eng, Stats) or equivalent experience.
• 4–8+ years building and shipping ML systems; staff level includes 3+ years leading multiple teams/systems.
• Deep experience in recommendation systems, ranking, or information retrieval at scale with latency constraints.
• Production DL in TensorFlow or PyTorch, including training, serving, and tuning on GPUs.
• Experience with Large Language Models and transformer architectures; embedding generation and deployment in latency-sensitive apps.
• Strong data engineering fundamentals: PySpark, Hive/SQL, Python pipelines; debugging and building features.
• Cloud ML infra (AWS/SageMaker or similar), deployment, and monitoring/observability.
• Proven technical leadership: mentoring, architecture reviews, influencing beyond own team.
• Strong communication of metrics, trade-offs, and business impact to technical and exec audiences.

Responsibilities

• Own the architecture of the ranking and recommendation stack end to end, including candidate retrieval and multi-objective ranking.
• Lead evolution of optimization objectives toward long-term value with offline and online evaluation.
• Introduce and apply state-of-the-art IR and RL techniques in production environments.
• Raise engineering standards: reproducible training, safe deployment, SLOs, observability, and debt management.
• Collaborate with Product, Search Eng, Ads, and Data Platform to align roadmaps and data needs.
• Mentor senior engineers, participate in hiring, and broaden technical depth across teams.
• Translate technical trade-offs into business terms for stakeholders; document rationale for durable decisions.

Skills

Information retrieval

Recommendation systems

Deep learning

Python

PyTorch

TensorFlow

Cloud ML

Education

MS/PhD in a quantitative discipline

Tools

SageMaker

CUDA

Spark/Hive

Job description

Wonder, based in New York, seeks a senior to senior staff ML engineer to own the full architecture of ranking and recommendation systems. You will guide model retrieval, multi-objective ranking, and calibration while collaborating with product and platform teams to ensure scalable, measurable impact.

You will drive state-of-the-art information retrieval and learning to rank techniques, mentor engineers, and communicate trade-offs to executives.