Machine Learning Engineer, Forecast Platform
Description For Machine Learning Engineer, Forecast Platform
DoorDash is seeking a Machine Learning Engineer to join their Forecast Platform team, focusing on improving the operational efficiency of their three-sided marketplace. This role offers a unique opportunity to impact millions of users by developing ML models that solve critical business challenges. The position requires expertise in building time-dependent statistical and ML models, with responsibilities spanning from feature creation to model maintenance. The ideal candidate should have advanced education (M.S. or PhD) with relevant experience in production ML systems. The role offers competitive compensation ranging from $137,100 to $299,300 based on level and location, along with comprehensive benefits including healthcare, equity grants, and paid parental leave. Working at DoorDash means joining a fast-paced environment where you'll contribute to building the world's most reliable on-demand logistics engine for delivery, supporting projects across supply/demand matching, infrastructure scaling, and support optimization. The company values diversity, inclusion, and provides a collaborative environment where team members can make significant impact while growing their careers in a hyper-growth setting.
Responsibilities For Machine Learning Engineer, Forecast Platform
- Build time-dependent statistical and ML models for matching supply/demand, predicting support needs, and providing insights
- Own the modeling life cycle end-to-end including feature creation, model development, experimentation, and maintenance
- Contribute to the development of in-house Forecasting Self-Service Platform
- Research new tools within the Forecasting space (e.g. TimeGPT, LLM extensions)
- Auto-scale infrastructure and optimize business processes
Requirements For Machine Learning Engineer, Forecast Platform
- M.S. and 3+ or PhD. and 1+ year(s) experience of developing advanced statistical and machine learning models in production
- Demonstrated expertise with object-oriented programming and ML Libraries, e.g. python, SciKit Learn, Lightgbm, Spark MLLib, PyTorch, TensorFlow
- Deep understanding of complex systems such as Marketplaces
- Domain knowledge in Machine Learning, Causal Inference, Operations Research, Forecasting
- Experience of shipping production-grade ML models and optimization systems
Benefits For Machine Learning Engineer, Forecast Platform
- Premium healthcare benefits
- Wellness expense reimbursement
- 16 weeks paid parental leave
- 401(k) plan with employer matching
- Commuter benefits
- Flexible vacation (for salaried roles)
- 11 paid holidays
- Disability and life insurance
- Family-forming assistance
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