Senior Staff Machine Learning Engineer

Experteer Overview In this senior, hands-on technical leadership role, you own the end-to-end machine learning stack behind Discovery, driving ranking, recommendation, and retrieval that influence what diners see. You shape architecture across multiple models, collaborate with product and platform teams, and raise the bar on evaluation, deployment, and observability. You bring state-of-the-art IR and recommender research into production, balancing conversion with long-term diner value. You’ll mentor engineers and influence cross-team decisions with clear technical rationale. Compensation / Benefits * Own the end-to-end architecture of the ranking and recommendation stack, including candidate retrieval, multi-objective ranking, calibration, and ensemble design * Evolve optimization objectives from short-term conversion to long-term diner value with offline evaluation and online experimentation * Incorporate state-of-the-art IR and recommender research into runtime systems (LLMs, embedding-based retrieval, sequential user representations) and assess transfer to production * Raise engineering and operational standards across teams (model evaluation, reproducible pipelines, safe deployment, SLOs, observability, technical debt management) * Partner with Product, Search Engineering, Ads, and Data Platform to shape roadmaps and ensure necessary data and infrastructure exist * Mentor senior and mid-level engineers, participate in hiring, and broaden the technical depth of the team * Translate technical trade-offs into business terms for product and executive stakeholders, documenting rationale for long-lasting decisions * Challenge assumptions, seek new innovations, and relentlessly improve system performance and business impact Tasks * 8+ years building and shipping ML systems with 3+ years at staff level or equivalent scope * Deep experience in large-scale recommendation, ranking, or information retrieval systems * Proven production experience with TensorFlow or PyTorch (training, serving, tuning on GPUs) * Experience with Large Language Models and transformer-based architectures (fine-tuning, embeddings, latency-aware deployment) * Strong data engineering fundamentals (PySpark, Hive/SQL, Python data stack) and feature engineering pipelines * Experimentation fluency: designing A/B tests and robust guardrails * Experience with cloud ML infrastructure (AWS/SageMaker or equivalent), deployment, and monitoring * Demonstrated technical leadership: mentoring, cross-team design reviews, influencing without authority * Strong ability to communicate performance metrics, trade-offs, and technical rationale to technical and non-technical audiences * Ability to stay current with research and translate into production systems * Strong self-motivation for continuous learning * Comfort with hybrid work expectations (3 days in office, up to 5) * Availability of salary range: New York: $240,000 - $249,500 per year Key requirements * equity and 401(k) * medical, dental, vision plans * paid time off including flexible time off * paid parental leave * disability coverage * discounted meals

192716 retrieval, sequential user representations) and assess transfer to production * Raise engineering and operational standards across teams (model evaluation, reproducible pipelines, safe deployment, SLOs, observability, technical debt management) * Partner with Product, Search Engineering, Ads, and Data Platform to shape roadmaps and ensure necessary data and infrastructure exist * Mentor senior and mid-level engineers, participate in hiring, and broaden the technical depth of the team * Translate technical trade-offs into business terms for product and executive stakeholders, documenting rationale for long-lasting decisions * Challenge assumptions, seek new innovations, and relentlessly improve system performance and business impact Tasks * 8+ years building and shipping ML systems with 3+ years at staff level or equivalent scope * Deep experience in large-scale recommendation, ranking, or information retrieval systems * Proven production experience with TensorFlow or PyTorch aaaaaaaaz

_ serving, tuning on GPUs) * Experience with Large Language Models and transformer-based architectures (fine-tuning, embeddings, latency-aware deployment) * Strong data engineering fundamentals (PySpark, Hive/SQL, Python data stack) and feature engineering pipelines * Experimentation fluency: designing A/B tests and robust guardrails * Experience with cloud ML infrastructure (AWS/SageMaker or equivalent), deployment, and monitoring * Demonstrated technical leadership: mentoring, cross-team design reviews, influencing without authority * Strong ability to communicate performance metrics, trade-offs, and technical rationale to technical and non-technical audiences * Ability to stay current with research and translate into production systems * Strong self-motivation for continuous learning * Comfort with hybrid work expectations (3 days in office, up to 5) * Availability of salary range: New York: $240,000 - $249,500 per year Key requirements * equity and 401(k) * medical, dental, vision a into * paid time off including flexible time off * paid parental leave * disability coverage * discounted meals