DoorDash
Applied Machine Learning Engineer - Causal Inference Recommendation
DoorDash, Washington, DC, United States
Applied Machine Learning Engineer - Causal Inference Recommendation
Qualifications
- 3+ years of industry experience developing advanced machine learning models with business impact, and shipping ML solutions to production
- 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
- 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
Responsibilities
- Utilize our robust data and machine learning infrastructure to build recommendation systems and implement new AI solutions to expand restaurant selection and drive their growth
- Conceptualize, design, and evaluate A/ML solutions
- Demonstrate a strong command of production-level machine learning, collaborating with multi-disciplinary teams to set strategy and execute to grow our business
- 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 deployment, experimentation, monitoring and explainability, and model maintenance
Benefits
- Comprehensive benefits and perks including premium healthcare, wellness expense reimbursement, paid parental leave, and more
- Location-specific base salary range: $140,100—$210,100 USD
- Compensation may vary based on skills, prior relevant experience, and specific work location
- Opportunities for equity grants included