Staff Software Engineer, Machine Learning - Fraud

$201,900 - $302,900/Yr

Doordash - San Francisco, CA

Full-time - Senior

San Francisco, CA

Couriers and Messengers

About the position

The Risk Machine Learning team at DoorDash is at the forefront of developing advanced models that are integral to our anti-fraud systems, operating on a global scale across more than 20 countries. We are seeking a passionate Technical Leader in Machine Learning Engineering to join our team as a Staff Machine Learning Engineer. In this role, you will serve as a trusted advisor to both your manager and peers, extending your influence across various teams within and beyond your area of expertise. Your primary responsibility will be to shape the team's roadmaps, manage ambiguity, identify opportunities, and translate them into clear objectives. You will be accountable for the formation and delivery of the team's Objectives and Key Results (OKRs). Your contributions will have a significant impact as you conceptualize, design, implement, and validate algorithmic solutions aimed at preventing, detecting, and mitigating risks associated with Fraud, as well as enhancing Trust and Safety. You will be excited about the prospect of introducing transformative changes to our risking system. Your role will require a strong command of production-level machine learning, experience in solving end-user problems, and the ability to collaborate effectively with multi-disciplinary teams. You will focus on eliminating single points of failure, including yourself, and work to uplift the skills and effectiveness of your team members. Setting and upholding the highest standards of engineering excellence will be crucial, as you consistently identify areas for improvement and foster a culture of continuous growth. You will report directly to the engineering manager within our Risk Machine Learning team in the Operations Excellence organization.

Responsibilities

• Drive the long-term technical ML/AI vision in Fraud, a critical component of DoorDash's business.
• Develop state-of-the-art machine learning solutions.
• Partner with engineering and product leaders to shape the product roadmap.
• Mentor team members and lead cross-functional pods to create collective impact.

Requirements

• Experience leading a team of Machine Learning Engineers in solving complex problems.
• 7+ years of industry experience developing machine learning models and deploying ML solutions to production.
• Domain expertise in training deep neural networks, including transformers and multi-task learning models.
• Proficiency in at least one deep learning framework, such as PyTorch or TensorFlow.
• M.S. or PhD in Statistics, Computer Science, Math, Operations Research, Physics, Bioinformatics, Economics, or other quantitative fields.
• Familiarity with a JVM language (Kotlin/Scala).
• Familiarity with large language models (LLMs) and anomaly detection.

Nice-to-haves

• Fraud domain knowledge.

Benefits

• Healthcare benefits
• 401(k) plan including employer match
• Short-term and long-term disability coverage
• Basic life insurance
• Wellbeing benefits
• Paid time off
• Paid parental leave
• Several paid holidays
• Opportunities for equity grants