ML Engineer - Remote

About The Company

DoorDash is a leading technology and logistics company committed to empowering local economies by connecting consumers with their favorite local merchants. Since its inception, DoorDash has revolutionized the way people order and receive goods, initially focusing on food delivery and expanding into a comprehensive platform that facilitates the delivery of a wide range of products. Our mission is to enable seamless, reliable, and efficient delivery experiences that support the growth of small businesses and enhance customer satisfaction. With a focus on innovation, agility, and community impact, DoorDash continues to grow rapidly, leveraging cutting-edge technology to solve complex logistical challenges and create value for merchants, consumers, and delivery partners alike.

About The Role

As a Machine Learning Engineer within the DoorDash Drive team, you will play a pivotal role in developing and deploying end-to-end machine learning systems that optimize delivery logistics and enhance operational efficiency. Your responsibilities will include designing and implementing models for delivery ETA, pickup ETA, merchant prep-time prediction, and order release optimization. You will work on leveraging large-scale spatiotemporal, behavioral, and marketplace signals to improve prediction accuracy and decision-making processes. Additionally, you will explore advanced AI techniques such as deep learning, reinforcement learning, and multimodal AI, including large language models (LLMs) and vision-language models (VLMs), to create innovative product experiences. Collaborating closely with cross-functional teams, you will ensure that these models are effectively integrated into production environments, monitored, and iteratively improved based on rigorous experimentation and real-time feedback. This role offers a unique opportunity to address complex logistical challenges and contribute to the development of AI-native solutions that directly impact merchant, consumer, and dasher outcomes.

Qualifications

• 5+ years of industry experience building and deploying production machine learning systems with measurable business impact
• Bachelor’s, Master’s, or PhD in Computer Science, Data Science, or related field
• Proficiency in developing scalable ML models using frameworks such as PyTorch
• Experience with distributed data processing tools like Spark and workflow orchestration platforms such as Airflow
• Strong software engineering skills in Python and familiarity with modern ML infrastructure and tooling
• Deep expertise in at least one of the following areas: Deep Learning, Reinforcement Learning, Optimization/Operations Research, Large Language Models (LLMs), or Vision-Language Models (VLMs)
• Hands-on experience in applying machine learning to estimation, ranking, prediction, and decision-making problems at scale
• Experience with deploying, monitoring, and maintaining ML systems in production environments
• Knowledge of AI-assisted development tools (e.g., Codex, Claude Code, Cursor) is a plus
• Ability to work effectively in ambiguous environments with a focus on experimentation and iteration
• Strong collaboration skills across engineering, data science, and product teams
• Location or willingness to relocate to San Francisco, CA; Sunnyvale, CA; or Seattle, WA

Responsibilities

• Design, develop, and optimize machine learning models for delivery ETA, pickup ETA, merchant prep-time, and order release prediction to improve reliability and efficiency
• Leverage large-scale spatiotemporal, behavioral, and marketplace data to enhance model accuracy and robustness
• Apply reinforcement learning and optimization techniques to improve logistics decision-making and marketplace operations
• Develop AI-native product experiences utilizing LLMs and VLMs to verify orders, analyze images, and enhance quality signals
• Conduct rigorous online experiments, monitor model performance in production, and iterate to achieve continuous improvements
• Collaborate with software engineers, product managers, and data scientists to deploy scalable ML solutions
• Ensure the reliability, scalability, and maintainability of ML systems in production environments
• Stay current with emerging AI technologies and incorporate innovative techniques into existing workflows

Benefits

• Competitive salary within the market range
• Equity grants and stock options
• Comprehensive health, dental, and vision insurance plans
• 401(k) retirement plan with employer matching
• Paid parental leave (up to 16 weeks)
• Wellness benefits and mental health programs
• Paid time off and paid sick leave in accordance with local laws
• Paid holidays (11 per year)
• Disability and life insurance coverage
• Family-forming assistance programs
• Commuter benefits and wellness expense reimbursements
• Flexible work arrangements and a supportive, inclusive workplace culture

Equal Opportunity

DoorDash is committed to fostering an inclusive and diverse workplace where all employees and applicants are treated with fairness and respect. We do not discriminate based on race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, disability, veteran status, or any other protected category. We believe that a diverse workforce drives innovation and growth, and we actively encourage candidates from all backgrounds to apply. Our hiring and employment practices comply with all applicable laws and regulations, and we are dedicated to providing accommodations for individuals with disabilities throughout the recruitment process.