Software Engineer, Machine Learning - Ads Intelligence

New York City

Applications have closed

DoorDash

When you join our team, you join our dream: to grow and empower local economies. We’re focused on improvement—from moving faster to leveling up the quality of our product—and our work is never complete. If you’re looking to define your career...

View company page

DoorDash is looking for top-class machine learning engineers to build reliable, scalable, and data-driven solutions to empower the intelligence of the rapid-growing DoorDash advertising platform.

About the Role

Machine learning engineers on the Ads team have the opportunity to dive into a wealth of consumer and merchant data, and leverage advanced machine learning techniques to maximize the value for our consumers, advertisers, and DoorDash.

You're excited about this opportunity because you will...
  • Develop advanced machine learning models to improve ads efficiency and quality.
  • Design and build optimization algorithms for budget pacing and automated bidding to achieve various advertising goals. 
  • Establish a data-driven framework to understand how the bid density and market competitiveness would affect advertising value and platform revenue. 
  • Develop new data solutions (eg. embeddings and consumer profiles) to target the relevant audience.
  • Be responsible for the end-to-end ML lifecycle, including ideation, offline model training, online shadowing/deployment, experimentation, and post-launch monitoring/measurement.
  • Build and extend the current data/ML infrastructure to empower Ads data applications including data analysis, ML modeling, and experimentation.
  • Scale our systems and services to fuel the growth of our business.
We're excited about you because you have...
  • M.S., or PhD. in a technical field such as computer science, mathematics, statistics, physics or equivalent.
  • 2+ years ML industry experience with a solid understanding of machine learning algorithms and fundamentals.
  • Experience building data/feature engineering pipelines at scale using Pyspark and Snowflake SQL.
  • Experience with building machine learning systems in production by using frameworks such as PyTorch, Keras, lightgbm, scikit-learn, Spark ML, or related.
  • Experiences in any of the following areas are preferred but not required:
    • Online advertising
    • Search relevance & ranking
    • Recommendation system
About DoorDash

At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users—from Dashers to merchant partners to consumers. We are a technology and logistics company that started with door-to-door delivery, and we are looking for team members who can help us go from a company that is known for delivering food to a company that people turn to for any and all goods. 

DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their unique perspectives, solve new challenges, and own their careers. We're committed to supporting employees’ happiness, healthiness, and overall well-being by providing comprehensive benefits and perks including premium healthcare, wellness expense reimbursement, paid parental leave and more.

Our Commitment to Diversity and Inclusion

We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel. 

Statement of Non-Discrimination: In keeping with our beliefs and goals, no employee or applicant will face discrimination or harassment based on: race, color, ancestry, national origin, religion, age, gender, marital/domestic partner status, sexual orientation, gender identity or expression, disability status, or veteran status. Above and beyond discrimination and harassment based on “protected categories,” we also strive to prevent other subtler forms of inappropriate behavior (i.e., stereotyping) from ever gaining a foothold in our office. Whether blatant or hidden, barriers to success have no place at DoorDash. We value a diverse workforce – people who identify as women, non-binary or gender non-conforming, LGBTQIA+, American Indian or Native Alaskan, Black or African American, Hispanic or Latinx, Native Hawaiian or Other Pacific Islander, differently-abled, caretakers and parents, and veterans are strongly encouraged to apply. Thank you to the Level Playing Field Institute for this statement of non-discrimination.

Pursuant to the San Francisco Fair Chance Ordinance, Los Angeles Fair Chance Initiative for Hiring Ordinance, and any other state or local hiring regulations, we will consider for employment any qualified applicant, including those with arrest and conviction records, in a manner consistent with the applicable regulation.

If you need any accommodations, please inform your recruiting contact upon initial connection.

Tags: Computer Science Data analysis Engineering Excel Feature engineering Keras LightGBM Machine Learning Mathematics ML models Model training PhD Physics Pipelines PySpark PyTorch Scikit-learn Snowflake Spark SQL Statistics

Perks/benefits: Career development Parental leave Wellness

Region: North America
Country: United States
Job stats:  0  0  0

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.