Applied Machine Learning Engineer - Causal Inference Recommendation

Doordash - Sunnyvale, CA

Full-time - Mid Level

Sunnyvale, CA

Couriers and Messengers

About the position

We're looking for a passionate Applied Machine Learning expert to join our team at DoorDash. In this role, you will utilize our robust data and machine learning infrastructure to build a recommendation system and implement new AI solutions to expand restaurant selection and drive their growth. You'll be conceptualizing, designing, and evaluating AI/ML solutions, demonstrating a strong command of production-level machine learning, and collaborating with multi-disciplinary teams to set the strategy and execute to grow our business. As an Applied Machine Learning Engineer, you will develop production machine learning solutions that serve as central intelligence to power multiple teams, including Sales Operations, Product, and Marketing. You will partner with engineering and product leaders to help shape the product roadmap leveraging AI/ML. Your responsibilities will include owning the modeling life cycle end-to-end, which encompasses feature creation, model development and deployment, experimentation, monitoring and explainability, and model maintenance. You will also find innovative ways to utilize diverse data sources and modeling techniques, such as NLP, ranking, personalization, image classification, and entity resolution, to engage with merchants at the right time and provide an AI-driven world-class merchant experience.

Responsibilities

• Develop production machine learning solutions that power multiple teams including Sales Operations, Product, and Marketing.
• Partner with engineering and product leaders to 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.
• Utilize diverse data sources and modeling techniques such as NLP, ranking, personalization, image classification, and entity resolution to enhance merchant engagement.

Requirements

• 1+ years of industry experience post PhD or 3+ years of industry experience post graduate degree in developing machine learning models with business impact.
• Expertise in applied ML for Causal Inference and Recommendation Systems, both classical and deep learning based.
• M.S. or PhD in Statistics, Computer Science, Economics, Math, Operations Research, Physics, or other quantitative fields.
• Ability to communicate technical details to non-technical stakeholders.
• Strong machine learning background in Python; experience with Spark, PyTorch or TensorFlow preferred.
• Familiarity with Kotlin/Scala.

Nice-to-haves

• Experience with experimentation, computer vision, and LLMs.
• A growth-minded and collaborative mindset.

Benefits

• Comprehensive healthcare benefits including premium healthcare and wellness expense reimbursement.
• 401(k) plan including an employer match.
• Short-term and long-term disability coverage.
• Basic life insurance.
• Paid time off and paid parental leave.
• Several paid holidays.
• Opportunities for equity grants.