Machine Learning Engineer, Forecast Platform - Sunnyvale, CA, United States - doordash

Description

Come help us build the world's most reliable on-demand, logistics engine for delivery We are bringing on a talented Machine Learning Engineer to help us improve the operational efficiency of DoorDash's three-sided marketplace of consumers, merchants, and dashers.

The Forecasting Platform provides a unique opportunity to have a broad impact on the business ensuring we can quickly respond to a rapidly changing operational environment.

The team supports projects across all of our major pillars (e.g. supply / demand, auto-scaling infrastructure, support optimization) as well as the development of an internal decision platform for time series.

As a Machine Learning Engineer, you will have the opportunity to leverage our robust data and machine learning infrastructure to develop ML models that impact millions of users across our three audiences and tackle our most challenging business problems.

You will work with other engineers, analysts, and product managers to develop and iterate on models to help us grow our business and provide the best service quality for our customers.

Build time-dependent statistical and ML models that solve product needs across our verticals - e.g. matching supply / demand, predicting support needs, providing insights to our internal platforms (ads, experiments, merchant), auto-scale infrastructure and optimize business processes such as promotions
Contribute to the development of our in-house Forecasting Self-Service Platform and proprietary Forecasting Repository to uplevel our capabilities
You can find out more on our ML blog post here
High-energy and confident — you keep the mission in mind, take ideas and help them grow using data and rigorous testing, show evidence of progress and then double down
S. and 3+ or PhD. and 1+ year(s) experience of developing advanced statistical and machine learning models in production
Demonstrated expertise with object-oriented programming and ML Libraries, e.g. python, SciKit Learn, Lightgbm, Spark MLLib, PyTorch, TensorFlow, etc
Machine Learning, Causal Inference, Operations Research, Forecasting
Experience of shipping production-grade ML models and optimization systems

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.

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.

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.

stereotyping) from ever gaining a foothold in our office.

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.

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.

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.

As part of the evaluation process we provide Covey with job requirements and candidate submitted applications.