Machine Learning Engineer
Description For Machine Learning Engineer
DoorDash is seeking a talented Machine Learning Engineer to join their team and help build the world's most reliable on-demand logistics engine for delivery. This role focuses on developing and improving ETA and Routing models that power DoorDash's three-sided marketplace of consumers, merchants, and dashers.
As a Machine Learning Engineer, you'll work on sophisticated deep learning models for next-generation ETA prediction and routing optimization. You'll have access to robust data and machine learning infrastructure to develop inference and optimization models that impact millions of users. The role involves end-to-end ownership of the modeling lifecycle, from feature creation to production deployment and maintenance.
The position requires strong expertise in Deep Learning, with hands-on experience using technologies like PyTorch, Spark, and Airflow in production environments. You'll need either 1+ years of post-PhD experience or 3+ years of post-graduate experience, along with a strong academic background in Computer Science, Statistics, or related fields.
DoorDash offers competitive compensation with base salary ranges from $137,100 to $299,300 USD, depending on level and location. The company provides comprehensive benefits including medical insurance, 401(k) with employer match, paid parental leave, and mental health support. This is an excellent opportunity for someone passionate about machine learning who wants to make a significant impact on a rapidly growing technology platform.
The role is based in either San Francisco or Seattle, where you'll work with cross-functional teams of data scientists, engineers, and product managers. You'll be at the forefront of solving complex problems in logistics and delivery optimization, directly contributing to DoorDash's mission of empowering local economies.
Responsibilities For Machine Learning Engineer
- Build Deep Learning models for next-generation ETA prediction
- Develop Machine Learning models in the routing space
- Own the modeling life cycle end-to-end including feature creation and model development
- Handle model testing, experimentation, monitoring and explainability
- Work on opportunities where ETA/Routing can benefit new business, markets, and regions
Requirements For Machine Learning Engineer
- M.S., or PhD. in Computer Science, Statistics, or other related quantitative fields
- 1+ years of industry experience post PhD or 3+ years of industry experience post graduate degree
- Strong background in Deep Learning and OSS ML technologies
- Experience with Spark, PyTorch, Airflow with hands-on production experience
- Expertise with Python and machine learning libraries
- Deep understanding of complex systems such as Marketplaces
- Experience shipping production-grade ML models and optimization systems
- Must be located or willing to relocate to San Francisco, CA, Sunnyvale, CA, or Seattle, WA
Benefits For Machine Learning Engineer
- 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
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