Staff Software Engineer, Machine Learning - Voice Ordering AI

$119,100 - $175,100/Yr

Doordash - San Francisco, CA

Full-time - Senior

Hybrid - San Francisco, CA

Couriers and Messengers

About the position

The Staff Machine Learning Engineer will play a crucial role in developing advanced machine learning solutions for DoorDash's grocery and retail delivery business. This position focuses on enhancing the catalog system and product knowledge graph through innovative algorithmic improvements, leveraging robust data and machine learning infrastructure to ensure accuracy and extensibility.

Responsibilities

• Develop production machine learning solutions to solve catalog building and quality problems such as entity recognition, entity resolution, attribute extraction, and category classification, image classification.
• Partner with engineering, product, and business strategy leaders to help shape an ML-driven product roadmap and grow a multi-billion dollar retail delivery business.
• Find new ways to use diverse data sources, intuitive models, and flexible experimentation to create a world-class shopping and dashing experience.

Requirements

• 8+ years of industry experience developing machine learning models with business impact, and shipping ML solutions to production.
• Experience with machine learning methods in building product knowledge graphs.
• Machine learning background in Python; experience with PyTorch, TensorFlow, or similar frameworks and familiarity with Natural Language Processing (LLM, Entity Recognition, Entity Resolution, Classification), Graph-based Models, and Computer Vision.
• M.S., or PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative fields.
• The desire for impact with a growth-minded and collaborative mindset.

Benefits

• 401(k) plan with an employer match
• Paid time off
• Paid parental leave
• Wellness benefits
• Paid holidays
• Medical benefits
• Dental benefits
• Vision benefits
• Disability insurance
• Basic life insurance
• Family-forming assistance
• Commuter benefit match
• Mental health program