Doordash - San Francisco, CA

posted about 1 month ago

Full-time - Senior
Hybrid - San Francisco, CA
Couriers and Messengers

About the position

As a Senior Software Engineer specializing in Machine Learning at DoorDash, you will play a pivotal role in enhancing our catalog system and product knowledge graph, which are essential components of our rapidly expanding grocery and retail delivery services. This position requires a deep understanding of applied machine learning, particularly in the areas of natural language processing (NLP) and graph-based models. You will be responsible for conceptualizing, designing, implementing, and validating algorithmic improvements that will directly impact the efficiency and accuracy of our catalog system. Your work will involve developing production-level machine learning solutions to address various catalog building and quality challenges, including entity recognition, entity resolution, attribute extraction, and category classification, as well as image classification. In this role, you will collaborate closely with cross-functional teams, including engineering, product management, and business strategy leaders, to shape an ML-driven product roadmap that supports the growth of our multi-billion dollar retail delivery business. You will leverage diverse data sources and intuitive models to create a seamless shopping experience for our users. The position is hybrid, allowing for a mix of in-office and remote work, and you will report directly to the engineering manager of the New Verticals, Catalog ML team.

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.
  • Collaborate with engineering, product, and business strategy leaders to shape an ML-driven product roadmap.
  • Utilize diverse data sources and intuitive models to enhance the shopping and delivery experience.
  • Implement new ML solutions to improve the accuracy and extensibility of the product knowledge graph.

Requirements

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

Nice-to-haves

  • Experience in a fast-paced startup environment.
  • Familiarity with cloud-based machine learning platforms.
  • Knowledge of data engineering practices.

Benefits

  • Comprehensive healthcare benefits including medical, dental, and vision insurance.
  • 401(k) plan with employer matching contributions.
  • Short-term and long-term disability coverage.
  • Basic life insurance.
  • Wellbeing benefits and wellness expense reimbursement.
  • Paid time off and paid parental leave.
  • Several paid holidays.
  • Opportunities for equity grants.
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