Machine Learning Engineer, Forecast Platform

$119,100 - $175,100/Yr

Doordash - Sunnyvale, CA

Full-time - Entry Level

Sunnyvale, CA

Couriers and Messengers

About the position

The Machine Learning Engineer role at DoorDash focuses on enhancing the operational efficiency of the company's logistics engine through the development of machine learning models. This position offers the opportunity to work on impactful projects that support the three-sided marketplace of consumers, merchants, and dashers, particularly through the Forecasting Platform. The role involves collaboration with engineers, analysts, and product managers to create models that address complex business challenges and improve service quality.

Responsibilities

• Build time-dependent statistical and ML models that solve product needs across various verticals.
• Own the modeling life cycle end-to-end including feature creation, model development, prototyping, experimentation, monitoring, explainability, and model maintenance.
• Contribute to the development of the in-house Forecasting Self-Service Platform and proprietary Forecasting Repository.
• Research new tools within the Forecasting space.

Requirements

• M.S. and 3+ years or PhD. and 1+ year(s) experience in developing advanced statistical and machine learning models in production.
• Demonstrated expertise with object-oriented programming and ML Libraries such as Python, SciKit Learn, Lightgbm, Spark MLLib, PyTorch, TensorFlow.
• Deep understanding of complex systems such as Marketplaces, and domain knowledge in Machine Learning, Causal Inference, Operations Research, or Forecasting.
• Experience in shipping production-grade ML models and optimization systems.

Nice-to-haves

• Experience with TimeGPT and LLM extensions.
• Familiarity with operational efficiency in logistics and delivery services.

Benefits

• 401(k) plan with employer match
• Paid time off
• Paid parental leave
• Wellness benefits
• Medical, dental, and vision benefits
• Disability and basic life insurance
• Family-forming assistance
• Commuter benefit match
• Mental health program
• Paid holidays