Machine Learning Engineer
Description For Machine Learning Engineer
DoorDash is seeking a talented Machine Learning Engineer to join their innovative DoorDash Labs team, an independent division focused on revolutionizing last-mile logistics through robotics and automation. This role offers an exceptional opportunity to impact millions of users across their three-sided marketplace of consumers, merchants, and dashers.
As a Machine Learning Engineer, you'll be at the forefront of developing sophisticated ML models that directly enhance the consumer experience. You'll work on critical challenges like reducing missing items, improving delivery time estimates, and optimizing order fulfillment. The role requires end-to-end ownership of the modeling lifecycle, from feature creation to production deployment and maintenance.
The ideal candidate brings 5+ years of industry experience (or 3+ years post-PhD) in developing machine learning models with demonstrable business impact. You should have an advanced degree in a quantitative field and deep expertise in modern ML frameworks and technologies. Your experience with production-grade ML systems and marketplace dynamics will be crucial for success.
DoorDash offers a competitive compensation package including a base salary range of $159,800 - $235,000 USD, equity grants, and comprehensive benefits. The company's culture emphasizes ownership, adaptability, and impact, making it an ideal environment for growth-minded professionals who thrive in fast-paced settings.
This role provides an unique opportunity to work on challenging problems at scale, with access to robust data infrastructure and the chance to shape the future of delivery logistics. You'll be part of a collaborative team that values innovation, rigorous testing, and data-driven decision making, while contributing to DoorDash's mission of empowering local economies.
Responsibilities For Machine Learning Engineer
- Build statistical and ML models that run in production to enhance consumer experience
- Own the modeling life cycle end-to-end including feature creation, model development and prototyping
- Handle experimentation, monitoring and explainability, and model maintenance
- Work with engineers, analysts, and product managers to develop and iterate on models
- Leverage data and machine learning infrastructure to develop inference and ML models
Requirements For Machine Learning Engineer
- M.S., or PhD. in Machine Learning, Statistics, Computer Science, Applied Mathematics or related quantitative fields
- 3+ years of industry experience post PhD or 5+ years of industry experience post graduate degree
- Expertise with programming languages, e.g. python, SciKit Learn, Lightgbm, Spark MLLib, PyTorch, TensorFlow
- Deep understanding of complex systems such as Marketplaces
- Experience shipping production-grade ML models and optimization systems
- Domain knowledge in Machine Learning, Causal Inference, Operations Research, Forecasting and Experimentation
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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