Applied Machine Learning Engineer - Causal Inference Recommendation Join to apply for the Applied Machine Learning Engineer - Causal Inference Recommendation role at DoorDash Applied Machine Learning Engineer - Causal Inference Recommendation Join to apply for the Applied Machine Learning Engineer - Causal Inference Recommendation role at DoorDash Get AI-powered advice on this job and more exclusive features. About The Team Come help us build the world's most reliable on-demand, logistics engine for last-mile retail delivery! We're looking for an experienced machine learning engineer to help us develop the AI/ML to power DoorDash expand Merchant selection and growing Merchants. About The Team Come help us build the world's most reliable on-demand, logistics engine for last-mile retail delivery! We're looking for an experienced machine learning engineer to help us develop the AI/ML to power DoorDash expand Merchant selection and growing Merchants. About The Role We’re looking for a passionate Applied Machine Learning expert to join our team. In this role, you will utilize our robust data and machine learning infrastructure to build recommendation system, and implementing new AI solutions to expand restaurants selection and drive their growth. You’ll be conceptualizing, designing, and evaluating A/ML solution. You will be expected to demonstrate a strong command of production-level machine learning, a passion to collaborate with multi-disciplinary teams to set the strategy and execute to grow our business. You’re Excited About This Opportunity Because You Will… Develop production machine learning solutions, which is a central intelligence to power multiple teams including Sales Operation, Product, and Marketing Partner with engineering and product leaders to help shape the product roadmap leveraging AI/ML. Own the modeling life cycle end-to-end including feature creation, model development and deployement, experimentation, monitoring and explainability, and model maintenance. Find new ways to use diverse data sources, and modeling techniques, such as NLP, ranking, personalization, image classification, and entity resolution to touch base with merchants at the right time and provide AI driven world class merchant experience. You can find out more on our ML blog here We’re Excited About You Because You Have… 1+ years of industry experience post PhD or 3+ years of industry experience post graduate degree of developing machine learning models with business impact Expertise in applied ML for Causal Inference and Recommendation Systems - both classical and deep learning based. Additional familiarity with experimentation, computer vision, and LLMs! M.S., or PhD. in Statistics, Computer Science, Economics, Math, Operations Research, Physics, or other quantitative fields. Ability to communicate technical details to nontechnical stakeholders Strong machine learning background in Python; experience with Spark, PyTorch or TensorFlow preferred. Familiarity with Kotlin/Scala. 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 The desire for impact with a growth-minded and collaborative mindset Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only 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 in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024. The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey Compensation The successful candidate's starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future. In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information. DoorDash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others. To learn more about our benefits, visit our careers page here. See Below For Paid Time Off Details For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year. For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week). The national base pay ranges for this position within the United States, including Illinois and Colorado. I4
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