Machine Learning Engineer - Conversation AI
DoorDash
About the Team Come help us build the world's most reliable on-demand, logistics engine for delivery! We're looking for an experienced ML Engineer to help us develop and improve the models that power DoorDash's three-sided marketplace of consumers, merchants, and dashers. Team is responsible for building a leading industry level NLP/LLM system to empower all communication for Doordash Journey, also building recommendation/personalization to provide best experience. About the Role As a Machine Learning Engineer you will have the opportunity to identify and prioritize machine learning investments across our conversation AI & personalization ecosystem. You will leverage our robust data and infrastructure to develop natural language processing and personalization models that impact millions of users across our three audiences. You will partner with an engineering lead and product manager to set the strategy that moves the business metrics which help us grow our business. You’re excited about this opportunity because you will Lead the development of DoorDash's support chatbot & LLM system: Applying LLM, active learning, semi-supervised learning, weak label generation, documentation embedding/retrieval and data augmentation strategies to improve the consumer, dasher, and merchant support experience Drive the personalization of DoorDash's issue prediction & resolution policies: Using both personalization, recommendation and dynamic pricing modeling technologies to serve millions of customers on personalized prediction resolution for any issues they might encounter during their journey Spearhead the creation of next-generation LLM AI Agent tools: Building Co-pilot system to evolve how millions of users interact with our support system Apply stratification, variance reduction, and other advanced experiment design techniques to create A/B tests to efficiently measure the impact of your innovations while minimizing risk to the broader system You can find out more on our ML blog here We’re excited about you because you have 3+ years of industry experience developing optimization models with business impact, including 1+ year(s) of industry experience serving in a tech lead role M.S., or PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative field You must be located near one of our engineering hubs which includes: San Francisco, Sunnyvale, Los Angeles, Seattle, and New York Deep understanding of natural language processing techniques and procedures for efficiently acquiring and validating human-labeled data Good experience in overall big data analysis, system, backed integration with new ML system/solution. Good understanding of quantitative disciplines such as statistics, machine learning, operations research, and causal inference Familiarity with programming languages e.g. python and machine learning libraries e.g. SciKit Learn, Spark MLLib Experience productionizing and A/B testing different machine learning models Familiarity with advanced causal inferences techniques and contextual bandit algorithms preferred 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. California Pay Range:
$140,100—$210,100 USD
Washington Pay Range:$140,100—$210,100 USD
If you need any accommodations, please inform your recruiting contact upon initial connection. 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. #J-18808-Ljbffr DoorDash- Machine Learning Engineer Intern (Conversational AI) - 2027 Start (PhD) Location: Seattle Employment Type: Intern Job Code: A218361A Responsibilities Agent runtime (harness / agent loop). Orchestrate skills, tools, and context; implement loop control & intervention, progressive...SuggestedInternship
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