Machine Learning Engineer - Delivery Excellence

DoorDash is seeking a Machine Learning Engineer to join their Delivery Excellence team, focusing on building the world's most reliable on-demand logistics engine for delivery. This role offers an exciting opportunity to work on fundamental challenges that directly impact DoorDash's three-sided marketplace of consumers, merchants, and dashers.

The position requires expertise in developing and implementing machine learning models that enhance service quality and customer experience. You'll be working with a robust data and ML infrastructure, tackling challenges like reducing cancellations, minimizing pickup waiting times, and improving delivery accuracy. The role combines technical expertise with business impact, as you'll be developing models that serve millions of users.

As a Machine Learning Engineer, you'll own the complete modeling lifecycle, from feature creation to production deployment and maintenance. The role offers exposure to various aspects of the business, including demand shaping, search ranking, and customer segmentation. You'll also have the opportunity to mentor other ML Engineers and contribute to the team's growth.

The compensation is highly competitive, ranging from $137,100 to $299,300 USD, depending on level and location, plus equity grants. DoorDash offers comprehensive benefits including medical, dental, vision coverage, 401(k) with matching, generous parental leave, and wellness programs.

The ideal candidate should have at least 3 years of industry experience (or 1+ post-PhD) in developing ML models with business impact, along with an advanced degree in a quantitative field. Strong programming skills, particularly in Python and modern ML frameworks, are essential. The role requires a combination of technical expertise, business acumen, and the ability to work effectively in a fast-paced startup environment.

Working at DoorDash means joining a mission-driven company that's transforming local economies, with the opportunity to solve complex technical challenges at scale while making a tangible impact on millions of users' daily lives.