Doordash

Leverage computer vision, NLP, GenAI, entity resolution, Deep Learning to create the best Consumer facing menus for Merchants.. M.S., or PhD. in Statistics, Computer Science, Economics, Math, Operations Research, Physics, or other quantitative fields.. Expertise in applied ML for computer vision, NLP, deep learning, embeddings, LLMs. Additional familiarity with experimentation and graph-based models!. Ability to communicate technical details to nontechnical stakeholdersStrong machine learning background in Python; experience with Spark, PyTorch or TensorFlow.. Familiarity with Kotlin/Scala.

machine learning engineer

About the RoleWe’re looking for a passionate Applied Machine Learning expert to join our team. In this role, you will utilize our robust data and machine learning infrastructure to build new AI solutions to optimize Merchant menus, the most important properties for both Merchant and Consumers. You’ll be conceptualizing, designing, and evaluating A/ML solution. You will be expected to demonstrate a strong command of production-level machine learning, a passion to collaborate with multi-disciplinary teams to lead the strategy and junior team member to execute.You’re excited about this opportunity because you will… Leverage computer vision, NLP, GenAI, entity resolution, Deep Learning to create the best Consumer facing menus for Merchants. Lead with engineering and product leaders to build ML-driven product roadmap.Own the modeling life cycle end-to-end including feature creation, model development and deployment, experimentation, monitoring and explainability, and model maintenance. Develop production machine learning solutions batch and realtime to provide the world class merchant experience.  You can find out more on our ML blog We’re excited about you because you have… 5+ years of industry experience developing machine learning models with business impact, and shipping ML solutions to production. M.S., or PhD. in Statistics, Computer Science, Economics, Math, Operations Research, Physics, or other quantitative fields.Expertise in applied ML for computer vision, NLP, deep learning, embeddings, LLMs. Additional familiarity with experimentation and graph-based models! Ability to communicate technical details to nontechnical stakeholdersStrong machine learning background in Python; experience with Spark, PyTorch or TensorFlow. Familiarity with Kotlin/Scala. You keep the mission in mind, take ideas and help them grow using data and rigorous testing, show evidence of progress and then double downThe desire for impact with a growth-minded and collaborative mindset

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