About the Team

At DoorDash, we're building the on-demand logistics engine of the future. We strive to empower local economies by helping businesses grow, creating flexible earnings opportunities, and connecting you to what you love. We are building foundational Data Platforms, ML Platform, Experimentation and Decision Systems /Frameworks which the product teams and various business analytics functions use to make timely, insightful and intelligent decisions that optimize our business and product. The AI/ML Platform team (as part of the overall Data AI Platform) focuses on building a best of breed ML Platform (a framework and all the tooling/solutions required) to unlock the power of AI for DoorDash’s business and product needs. The team owns all the infrastructure necessary to enable DoorDash data scientists and ML Engineers to quickly and efficiently apply machine learning. The platform covers the entire ML development lifecycle, which includes featuring engineering, feature store, model store, model training, model inference and ML observability, and more

About the Role

We’re looking for a passionate Engineering Leader in the Machine Learning domain to join our team. We’re looking for someone with a command of high/internet scale, production-level machine learning and experience working in a fast paced working environment with highly evolving needs. You will be managing a set of teams focused on specific areas of the ML ecosystem and work with the cross functional partners and stakeholders in this domain.

You’re excited about this opportunity because you will…

• Drive vision & strategy for taking the Machine Learning Platform from good to great!
• Bring your expertise in building and operating high scale systems with a focus on reliability and quality.
• Utilize your experience in managing and operating state of the art ML Models in production (in the area of classic ML as well as DNNs, Large Language Models/GenAI)
• Hire and manage a well run, successful team via coaching, mentoring and providing technical and career guidance.
• Build, sustain, and grow a diverse team to address the growing needs of the organization.
• Collaborate with stakeholders building solutions on top of the platform
• Create and foster a positive and supportive work culture.

We’re excited about you because you have…

• 10 years of industry experience developing machine learning models with business impact, and shipping ML solutions to production.
• Are curious about and have interests in deep learning, and fine-tuning.
• Have familiarity and experience with Spark, PyTorch or TensorFlow (and similar ML frameworks and libraries).
• You must be located near one of our engineering hubs which includes: San Francisco, Sunnyvale, or Seattle.
• M.S., or PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative field is a plus
• Familiarity with Distributed Systems and Infrastructure (using a Cloud provider such as AWS/GCP or Azure) is a great advantage

Compensation

The location-specific base salary range for this position is listed below. Compensation in other geographies may vary.

Actual compensation within the pay range will be decided based on factors including, but not limited to, skills, prior relevant experience, and specific work location. For roles that are available to be filled remotely, base salary is localized according to employee work location. Please discuss your intended work location with your recruiter for more information.

DoorDash cares about you and your overall well-being, and that’s why we offer a comprehensive benefits package, for full-time employees, that includes healthcare benefits, a 401(k) plan including an employer match, short-term and long-term disability coverage, basic life insurance, wellbeing benefits, paid time off, paid parental leave, and several paid holidays, among others.

In addition to base salary, the compensation package for this role also includes opportunities for equity grants.

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on June 20, 2024.

Please see the independent bias audit report covering our use of Covey here.