Applied Machine Learning Engineer
Description For Applied Machine Learning Engineer
DoorDash is seeking an experienced Applied Machine Learning Engineer to join their team and help build the world's most reliable on-demand logistics engine for last-mile retail delivery. In this role, you will utilize robust data and machine learning infrastructure to develop AI solutions that optimize Merchant menus, a critical aspect for both Merchants and Consumers.
Key responsibilities include:
- Leveraging computer vision, NLP, GenAI, entity resolution, and Deep Learning to create the best Consumer-facing menus for Merchants.
- Leading ML-driven product roadmap development with engineering and product leaders.
- Owning the entire modeling lifecycle, from feature creation to model deployment, experimentation, monitoring, and maintenance.
- Developing production machine learning solutions, both batch and real-time, to provide world-class merchant experiences.
The ideal candidate will have:
- 5+ years of industry experience developing impactful machine learning models and shipping ML solutions to production.
- M.S. or Ph.D. in a quantitative field such as Statistics, Computer Science, Economics, Math, Operations Research, or Physics.
- Expertise in applied ML for computer vision, NLP, deep learning, embeddings, and LLMs, with additional familiarity in experimentation and graph-based models.
- Strong communication skills to convey technical details to non-technical stakeholders.
- Proficiency in Python for machine learning, with experience in Spark, PyTorch, or TensorFlow.
- Familiarity with Kotlin/Scala.
DoorDash offers a comprehensive benefits package, including a 401(k) plan with employer match, paid time off, parental leave, wellness benefits, and medical, dental, and vision coverage for full-time employees. The company is committed to diversity, inclusion, and creating an environment where all team members can excel and make impactful decisions.
Join DoorDash to be part of a rapidly growing company that's expanding beyond food delivery to become the go-to platform for any and all goods.
Responsibilities For Applied Machine Learning Engineer
- Leverage computer vision, NLP, GenAI, entity resolution, Deep Learning to create the best Consumer facing menus for Merchants
- Lead with engineering and product leaders to build ML-driven product roadmap
- Own the modeling life cycle end-to-end including feature creation, model development and deployment, experimentation, monitoring and explainability, and model maintenance
- Develop production machine learning solutions batch and realtime to provide the world class merchant experience
Requirements For Applied Machine Learning Engineer
- 5+ years of industry experience developing machine learning models with business impact, and shipping ML solutions to production
- M.S., or PhD. in Statistics, Computer Science, Economics, Math, Operations Research, Physics, or other quantitative fields
- Expertise in applied ML for computer vision, NLP, deep learning, embeddings, LLMs
- Ability to communicate technical details to nontechnical stakeholders
- Strong machine learning background in Python; experience with Spark, PyTorch or TensorFlow
- Familiarity with Kotlin/Scala
Benefits For Applied Machine Learning Engineer
- 401k
- Paid time off
- Paid parental leave
- Wellness benefits
- Medical Insurance
- Dental Insurance
- Vision Insurance
- Disability insurance
- Life insurance
- Family-forming assistance
- Commuter benefits
- Mental health program
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