About the Role
As a Machine Learning Engineer, you will have the opportunity to leverage our robust data and machine learning infrastructure to develop inference and optimization ETA and Routing models that impact millions of users across our three audiences and tackle our most challenging business problems.
You will work with other data scientists, engineers, and product managers to develop and iterate on models to help us grow our business and provide better service quality for our customers.
You’re excited about this opportunity because you will
- Build Deep Learning models for next-generation ETA that provide the most accurate, scalable and robust time predictions and enhance the consumer experience.
- Build Machine Learning models in the routing space, which can be used as the single source of truth across internal teams to positively impact the top-line business metrics.
- Own the modeling life cycle end-to-end including feature creation, model development and testing, experimentation, monitoring and explainability, and model maintenance.
- Being exposed to new opportunities where ETA / Routing can be used as a lever that benefits new business, new markets, and new regions.
- You can find out more on our ML blog post .
We’re excited about you because
- High-energy and confident 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
- You’re an owner driven, focused, and quick to take ownership of your work
- Humble you’re willing to jump in and you’re open to feedback
- Adaptable, resilient, and able to thrive in ambiguity things change quickly in our fast-paced startup and you’ll need to be able to keep up!
- Growth-minded you’re eager to expand your skill set and excited to carve out your career path in a hyper-growth setting
- Desire for impact ready to take on a lot of responsibility and work collaboratively with your team
Experience
- 1+ years of industry experience post PhD or 3+ years of industry experience post graduate degree of developing advanced machine learning models with business impact.
- M.S., or PhD. in Computer Science, Statistics, or other related quantitative fields.
- Strong background in Deep Learning and OSS ML technologies such as Spark, PyTorch, Airflow with hands-on experience in production.
- Demonstrated expertise with programming languages e.g. python and machine learning libraries e.g. LightGBM, Spark MLLib, PyTorch, etc.
- Deep understanding of complex systems such as Marketplaces, and domain knowledge in two or more of the following : Deep Learning, Reinforcement Learning, Operations Research, and Forecasting.
- Experience of shipping production-grade ML models and optimization systems, and designing sophisticated experimentation techniques.
- You are located or are planning to relocate to San Francisco, CA, Sunnyvale, CA, or Seattle, WA
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