Machine Learning Engineer

Own end-to-end machine learning architecture for search ranking and personalized recommendations in New York.

Responsibilities

• Lead the architecture of the ranking and recommendation stack end to end, including candidate retrieval, multi-objective ranking, calibration, and an ensemble that balances conversion against profitability
• Make cross-system design decisions that individual model owners cannot complete alone
• Drive the evolution of the optimization objective from short-term conversion toward long-term diner value, including required offline evaluation and online experimentation to build confidence before release
• Integrate state-of-the-art research into runtime systems for information retrieval and recommender systems, including:
  • LLM-driven query and intent understanding
  • embedding-based retrieval
  • sequential user representations for cold start
  • real-time inference
• Evaluate rigorously what transfers to production traffic and decline approaches that do not
• Raise engineering and operational standards across multiple teams, covering:
  • model evaluation and scorecards
  • reproducible training pipelines
  • safe deployment
  • SLOs and observability for tier-1 models
  • proactive technical debt management
• Partner with Product, Search Engineering, Ads, and the Data Platform to shape roadmaps, surface risk early, and ensure data and infrastructure exist before model needs are imminent
• Mentor senior and mid-level engineers, participate in hiring, and grow technical depth so critical systems do not depend on a single person
• Translate technical trade-offs into business terms for product and executive stakeholders and document the rationale clearly
• Question existing assumptions, identify innovations not yet pursued, and continuously improve business performance through deep analysis

Requirements

• MS/PhD in a quantitative discipline (Computer Science, Math, Physics, Engineering, Statistics or other technical field) or equivalent experience
• 4-8+ years building and shipping machine learning systems
• For staff level and above: 3+ years operating at senior scope, setting technical direction across multiple teams, model families, or systems
• Deep experience in recommendation systems, ranking, or information retrieval at scale with production constraints for latency and cost
• Production deep learning experience with TensorFlow or PyTorch, including training, serving, and tuning runtime models on GPUs
• Experience with Large Language Models and transformer-based architectures, including fine-tuning, embedding generation, and deploying in latency-sensitive applications
• Language understanding over imperfect grammar (real-world search queries, menu and catalog text) is a strong plus
• Strong data engineering fundamentals: PySpark, Hive/SQL, Python data stack, and debuggable feature pipelines
• Experimentation fluency: designing A/B tests, selecting guardrails, and recognizing when offline metrics mislead
• Experience with cloud ML infrastructure (AWS/SageMaker or equivalent), model deployment, and production monitoring and observability
• Demonstrated technical leadership: mentoring engineers, driving architecture reviews beyond your team, and influencing decisions without direct authority
• Ability to communicate performance metrics, model behavior, and technical trade-offs to technical and non-technical audiences, including executives
• Ability to keep up with the latest research publications and synthesize them into production systems
• Deep interest in self-directed continuous learning

Technologies

• TensorFlow, PyTorch, GPUs
• Large Language Models, transformer-based architectures
• PySpark, Hive/SQL, Python
• AWS, SageMaker
• A/B tests

Benefits

• Competitive compensation package with equity
• 401(k)
• Choice of medical, dental, and vision plans
• Company paid short and long term disability coverage
• Paid time off including flexible time off for exempt employees
• Paid vacation for non-exempt employees
• Paid sick leave in compliance with applicable law
• Paid parental leave
• Discounted meals and exclusive perks across the Wonder family of brands

Compensation

• Senior MLE (New York base): $176,000 - $191,000
• Staff MLE (New York base): $208,500 - $225,000
• Senior Staff MLE (New York base): $240,000 - $260,000

Wonder participates in the federal government’s E-Verify program to confirm employment eligibility. If you need an accommodation during the interview process, inform your recruiter. Interviews will be scheduled and candidacy information shared via email or text.