Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Tier-1 brand and metro location increase candidate density, but senior ML leadership narrows the pool.
Requires deep ML/AI, NLP, LLM, and ads recommender expertise, limiting cross-industry transferability.
Explicit 14+ years and deep ML/AI, NLP, LLM, and production systems requirements make shortlisting highly strict.
Lead a team of applied researchers and engineers focused on NLP, large language models, recommender systems, and ML production engineering at scale.
Set technical direction and drive deployment of production ML systems that improve buyer experience, seller success, marketplace growth, and advertising performance.
Collaborate cross-functionally with product, design, analytics, engineering, and business teams to develop scalable AI-driven ads and discovery solutions.
9+ years (PhD), 12+ years (MS), or 14+ years (BS) in Engineering, Machine Learning, or AI research roles.
Experience leading engineering or research teams in ML/AI environments.
Strong expertise in machine learning, NLP, LLMs, recommender systems, and production ML systems.
Proficiency in object-oriented programming languages such as Scala or Java and experience with cloud-based, distributed production systems.
Experienced in managing high-performing applied research and engineering teams in industrial AI/ML settings with measurable business impact.
Technically deep with hands-on experience and strategic ability to set execution standards and technical direction in ML production.
Skilled at cross-functional leadership partnering effectively with product, design, analytics, engineering, and business stakeholders to turn ambiguous opportunities into scalable solutions.