1 day ago
Base Salary
$209k - $217k/yr
Responsibilities
- Own the architecture of ranking and recommendation systems across candidate retrieval, multi-objective ranking, calibration, and ensemble optimization.
- Lead improvements to optimization objectives, offline evaluation, online experimentation, and long-term value measurement.
- Apply research in information retrieval and recommender systems, including LLM-driven query understanding, embeddings, sequential user representations, and real-time inference.
- Raise standards for model evaluation, scorecards, reproducible training pipelines, safe deployment, SLOs, observability, and technical debt management.
- Partner with Product, Search Engineering, Ads, and Data Platform to shape roadmaps and ensure data and infrastructure readiness.
- Mentor senior and mid-level engineers, conduct design and code reviews, participate in hiring, and grow team technical depth.
- Communicate technical trade-offs, model behavior, and performance metrics to technical, non-technical, and executive stakeholders.
Requirements
- MS or PhD in a quantitative discipline such as Computer Science, Math, Physics, Engineering, or Statistics, or equivalent experience.
- 6+ years building and shipping machine learning systems, including 3+ years operating at senior-level scope across multiple teams, model families, or systems.
- Deep production experience with recommendation systems, ranking, or information retrieval at scale under latency and cost constraints.
- Proven production deep learning experience with TensorFlow or PyTorch, including training, serving, and GPU-based runtime tuning.
- Experience with large language models and transformer architectures, including fine-tuning, embedding generation, and deployment in latency-sensitive applications.
- Strong data engineering fundamentals with PySpark, Hive/SQL, the Python data stack, and debuggable feature pipelines.
- Experience designing A/B tests, selecting guardrails, and evaluating the limitations of offline metrics.
- Experience with cloud ML infrastructure such as AWS/SageMaker or an equivalent platform, model deployment, monitoring, and observability.
- Demonstrated technical leadership through mentoring, architecture reviews, cross-team influence, and decision-making without direct authority.
- Ability to synthesize research publications into production systems and communicate effectively with technical and non-technical stakeholders.
- Experience with language understanding over imperfect grammar is a strong plus.
Benefits
- Hybrid work model requiring 3 days per week in the office, with the option and encouragement to work onsite up to 5 days per week.
- Competitive compensation package with equity and a 401(k).
- Medical, dental, and vision plan options, plus company-paid short- and long-term disability coverage.
- Paid time off, flexible time off for exempt employees, paid vacation for non-exempt employees, and paid sick leave as required by law.
- Paid parental leave, discounted meals, and exclusive perks across the Wonder family of brands.
Categories
About Grubhub
Grubhub builds an online marketplace and logistics network for ordering takeout and delivery from local restaurants across the U.S. It earns commissions and delivery fees, and offers consumer subscriptions and corporate solutions. Founded in 2004 and headquartered in Chicago, it is part of Wonder Group and lists hundreds of thousands of merchants across 4,000+ cities.