About the Team

Be part of our team in building the most reliable on-demand logistics platform for last-mile grocery and retail delivery. We are looking for an experienced and talented AI Engineer for Retail Growth to lead the innovation of cutting-edge ML models that power DoorDash’s rapidly growing grocery and retail business. As an AI Engineer for Retail Growth, you will play a pivotal role in shaping the future of our retail delivery platform.

About the Role

As a machine learning engineer, you will design, develop, and implement algorithmic enhancements to the classification, fulfillment, and catalog systems that are core to our business. You will leverage our solid data infrastructure to build solutions that improve the customer shopping experience, fulfillment speed, and knowledge graph accuracy. We believe in teamwork and want someone with production-level ML expertise and an interest in solving real-world problems in a multidisciplinary setting.

Key Responsibilities

Build production-level machine learning models for shopping and delivery problems, including recommendation systems, search optimization, and product knowledge graphs. Also improve system performance.
Work closely with product, engineering, and business strategy teams. This influences the ML-based product roadmap. In addition, it helps build a multibillion-dollar retail company.
Use diverse data sources, simple models, and flexible experiments. As a result, continuously improve the delivery and shopping experience. To this end, improve system performance and user interaction.

What we’re looking for

Firstly, minimum 1 year of post-PhD work experience or 3+ years of work experience post-graduate degree, with experience in building high-impact machine learning models.
Secondly, there is a need for there to be sharp acquaintance with machine learning techniques such as recommender systems, search, optimization, time series, and natural language processing.
In addition, Python proficiency and experience with ML platforms such as PyTorch, TensorFlow, or the like are required.
In addition, a Master’s or Ph.D. in Computer Science, Mathematics, Statistics, Operations Research, Physics, Economics, or any other quantitative discipline is needed.
Finally, a growth mentality and a willingness to make valuable contributions to the firm and to work effectively with cross-functional teams will be your secret to success.

Compensation and Benefits

Base salary within a range based on location and other criteria. Salary ranges are market-based and adjusted periodically.
Equity awards and a rich suite of benefits including medical, dental, and vision coverage, paid leave, paid parental leave, and wellness programs.
Additional benefits such as a 401(k) plan with match, traveler benefits, disability and life insurance, and family planning assistance.

About DoorDash

We enable local economies and are committed to eliminating the complexity of logistics and delivery issues at DoorDash. As we transition from a food delivery company to an end-to-end goods provider, our team members can contribute to driving innovation at an unprecedented pace. The well-being of our employees is a priority, supported by comprehensive benefits and perks that promote health, happiness, and work-life balance.

Our Commitment to Diversity and Inclusion

Creating a diverse, inclusive, and equitable work environment is one of our top priorities. We firmly believe that people from diverse backgrounds, experiences, and perspectives should collaborate to drive innovation. Candidates from underrepresented groups, such as women, non-binary, LGBTQIA+, veterans, and more, are always encouraged to apply.

Non-Discrimination Statement

DoorDash is an equal opportunity employer. We do not discriminate on the basis of race, gender, disability, or other protected characteristics, and we are strongly opposed to any form of inappropriate behavior within our office.

Accommodations

If you require an accommodation at any stage of our hiring process, please notify your recruiter. We are happy to accommodate modifications that ensure a smooth, accessible, and inclusive experience.

Frequently Asked Questions (FAQs) 

Q. What are the requirements for an AI engineer for a retail growth role?

A strong background in machine learning, proficiency in Python, and a Masters/PhD in a quantitative field are essential.

Q. What will make me different in this position?

You will build machine learning models that improve retail and delivery systems, make customers more satisfied, and improve efficiency.

Q. Will I work with other teams?

Yes, you will work with engineering, product, and business strategy teams to align machine learning solutions with objectives.

Q. Is remote work acceptable for this role?

This job is hybrid and involves some time in the office with the flexibility of working remotely.

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