What are the responsibilities and job description for the Machine Learning Engineer - New Verticals - Search & Recommendations position at DoorDash USA?
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 a talented machine learning engineer to help us develop the cutting edge search and information retrieval models that power DoorDash's growing retail and grocery business.
About the Role
We’re looking for a passionate Applied Machine Learning expert to join our team. As a Machine Learning Scientist, you’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the search and personalization experiences at the heart of our fast growing grocery and retail delivery business. In this role, you will leverage our robust data and machine learning infrastructure to implement new ML solutions to make the consumer search experience more relevant, seamless, and delightful across grocery, convenience, and many other retail categories. You will be expected to demonstrate a strong command of production level machine learning, a passion for solving end-user problems, leadership skills to collaborate well with multi-disciplinary teams, and execution focus to prioritize effectively in a dynamic environment.
You’re excited about this opportunity because you will…
- Develop production machine learning solutions to build a world class personalized shopping experience for a diverse and expanding retail space.
- Partner with engineering and product leaders to help shape the product roadmap leveraging ML.
- Mentor junior team members, and lead cross functional pods to generate collective impact.
- You can find out more on our ML blog here
We’re excited about you because you have…
- 5 years of industry experience developing machine learning models with business impact, and shipping ML solutions to production.
- Deep expertise in applied ML for Search/NLP/IR/RecSys - both classical and deep learning based. Additional familiarity with explore/exploit/MAB algorithms, LLMs, and causal inference techniques are a plus.
- Strong machine learning background in Python; experience with PyTorch or TensorFlow preferred.
- Familiarity with Kotlin/Scala are a plus.
- Great communication skills - written and verbal.
- M.S., or PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative field
- 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
- You’re an owner — driven, focused, and quick to take ownership of your work
- Humble — you’re willing to jump in and you’re open to feedback
- Adaptable, resilient, and able to thrive in ambiguity as things change quickly in our fast-paced environment!
- Growth-minded — you’re eager to expand your skill set and excited to carve out your career path in a hyper-growth setting
- Desire for impact — ready to take on a lot of responsibility and work collaboratively with your team
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