About the Role
We’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 develop inference and optimization for Merchant Experience and new merchant’s products, such as menu item tax categorization, inventory prediction, logistic service, catering.
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 and the team to execute.
You’re excited about this opportunity because you will
- Build Deep Learning models for logistic ETA that provide the most accurate, scalable and robust time prediction.
- Utilize deep learning and NLP to predict item categorization, and computer vision to improve non-restaurant delivery quality.
- Lead with engineering and product leaders to shape the product roadmap leveraging AI / ML.
- Own the modeling life cycle end-to-end including feature creation, model development and deployment, experimentation, monitoring and explainability, and model maintenance.
- Being exposed to new opportunities where AI / ML can be used as a lever that benefits new business, new markets, and new regions.
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 deep learning, computer vision, NLP. Additional familiarity with experimentation and LLMs is a plus!
- Ability to communicate technical details to nontechnical stakeholders
- Strong machine learning background in Python; experience with Spark, PyTorch or TensorFlow preferred.
- 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 down
- The desire for impact with a growth-minded and collaborative mindset
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