Senior Machine Learning Engineer

Salary: $240,000 - 249,500 per year Requirements:

• We seek an MS or PhD in a quantitative discipline such as Computer Science, Mathematics, Physics, Engineering, Statistics, or a related technical field, or equivalent practical experience.
• We require 8+ years of experience building and delivering machine learning systems, including 3+ years in staff-level roles setting technical direction across multiple teams, model families, or systems.
• We want deep expertise in recommendation systems, ranking, or information retrieval at scale, in production and under real latency and cost constraints.
• We expect proven experience with production deep learning in TensorFlow or PyTorch, including training, serving, and tuning runtime models on GPUs.
• We value experience with large language models and transformer-based architectures, including fine-tuning, embedding generation, and deployment in latency-sensitive applications; familiarity with language understanding over imperfect search queries and catalog text is a plus.
• We look for strong data engineering fundamentals, including PySpark, Hive/SQL, the Python data stack, and feature pipelines you can both debug and build.
• We require fluency with experimentation, including designing A/B tests, selecting appropriate guardrails, and recognizing when offline metrics are misleading.
• We look for experience with cloud ML infrastructure such as AWS/SageMaker or similar, along with model deployment, monitoring, and observability.
• We want demonstrated technical leadership, including mentoring engineers, driving design and architecture reviews beyond your own team, and influencing decisions without direct authority.
• We expect strong communication skills for discussing performance metrics, model behavior, and technical trade-offs with both technical and non-technical audiences, including executive stakeholders.
• We value the ability to stay current with research publications and translate them into working production systems.
• We look for a strong commitment to continuous learning and self-directed growth.

• We own the end-to-end architecture of our ranking and recommendation stack, including candidate retrieval, multi-objective ranking, calibration, and the ensemble balancing conversion with profitability.
• We lead the shift in our optimization objective from short-term conversion toward long-term diner value, including the offline evaluation and online experimentation needed to validate results before launch.
• We bring current research in information retrieval and recommender systems into production, including LLM-based query and intent understanding, embedding-driven retrieval, sequential user representations for cold start, and real-time inference.
• We raise engineering and operational standards across multiple teams through better model evaluation, scorecards, reproducible training pipelines, safe deployment practices, SLOs, observability for tier-1 models, and proactive technical debt management.
• We partner with Product, Search Engineering, Ads, and Data Platform to shape roadmaps, identify risks early, and ensure the required data and infrastructure are in place.
• We mentor senior and mid-level engineers, contribute to hiring, and strengthen the teams technical depth so critical systems are not dependent on a single individual.
• We translate technical trade-offs into business language for product and executive stakeholders, and document decisions clearly so the rationale endures.
• We challenge existing assumptions, look for untapped innovation, and continuously analyze and improve business performance.

• AWS
• Cloud
• Fine-tuning
• Hive
• LLM
• Machine Learning
• PyTorch
• Python
• PySpark
• SQL
• TensorFlow

More:

We are Grubhub, part of Wonder, and we connect people with the food they love through a leading U.S. ordering and delivery marketplace serving more than 415,000 merchants across 4,000+ cities. Our team is based in New York City, Chicago, and Denver, and this hybrid role requires three days per week in the office, with the option to come in more often if desired. We offer a competitive compensation package with equity and a 401(k), medical, dental, and vision coverage, company-paid short- and long-term disability, paid time off, paid parental leave, discounted meals, and exclusive perks across the Wonder family of brands. New York salary: $240,000 to $249,500 per year, with final pay depending on location, skills, education, training, credentials, and experience.

last updated 37 week of 2026